diff --git a/.github/dependency_review.yml b/.github/dependency_review.yml
index 5636a441501fc8..3240502f4e94b5 100644
--- a/.github/dependency_review.yml
+++ b/.github/dependency_review.yml
@@ -2,13 +2,10 @@ fail-on-severity: 'low'
 allow-licenses:
   - 'BSD-2-Clause'
   - 'BSD-3-Clause'
-  - 'BSD-2-Clause AND BSD-3-Clause'
-  - 'BSD-3-Clause AND BSD-3-Clause-Clear'
+  - 'BSD-3-Clause-Clear'
   - 'MIT'
   - 'Apache-2.0'
-  - 'Apache-2.0 AND BSD-3-Clause'
   - 'ISC'
-  - 'Apache-2.0 AND MIT'
   - 'BlueOak-1.0.0'
   - '0BSD'
   - 'Python-2.0'
diff --git a/.github/workflows/coverity.yml b/.github/workflows/coverity.yml
index e26bd66e097e33..5a08ec084dadac 100644
--- a/.github/workflows/coverity.yml
+++ b/.github/workflows/coverity.yml
@@ -85,7 +85,6 @@ jobs:
       image: ${{ fromJSON(needs.docker.outputs.images).ov_build.ubuntu_20_04_x64 }}
       volumes:
         - /mount:/mount
-      options: -e SCCACHE_AZURE_BLOB_CONTAINER -e SCCACHE_AZURE_CONNECTION_STRING
     env:
       DEBIAN_FRONTEND: noninteractive # to prevent apt-get from waiting user input
       CMAKE_BUILD_TYPE: 'Release'
@@ -95,14 +94,6 @@ jobs:
       OPENVINO_CONTRIB_REPO: /__w/openvino/openvino/openvino_contrib
       BUILD_DIR: /__w/openvino/openvino/openvino_build
       COVERITY_TOOL_DIR: /__w/openvino/openvino/coverity_tool
-      CMAKE_CXX_COMPILER_LAUNCHER: sccache
-      CMAKE_C_COMPILER_LAUNCHER: sccache
-      SCCACHE_IGNORE_SERVER_IO_ERROR: 1
-      SCCACHE_SERVER_PORT: 35555
-      SCCACHE_ERROR_LOG: /__w/openvino/sccache_log.txt
-      SCCACHE_LOG: warn
-      SCCACHE_AZURE_KEY_PREFIX: coverity_lin
-      SCCACHE_CACHE_SIZE: 50G
 
     steps:
       - name: Clone OpenVINO
@@ -141,8 +132,6 @@ jobs:
       #
       # Build
       #
-      - name: Clean sccache stats
-        run: ${SCCACHE_PATH} --zero-stats
         
       - name: CMake configure - OpenVINO
         run: |
@@ -165,9 +154,6 @@ jobs:
 
       - name: Cmake build - OpenVINO with Coverity
         run: ${COVERITY_TOOL_DIR}/cov-analysis*/bin/cov-build --dir ${BUILD_DIR}/cov-int cmake --build ${BUILD_DIR} --parallel $(nproc) --config ${{ env.CMAKE_BUILD_TYPE }}
-        
-      - name: Show sccache stats
-        run: ${SCCACHE_PATH} --show-stats
 
       - name: Pack Artefacts
         run: tar -cvf - cov-int | pigz > openvino.tgz
diff --git a/.github/workflows/fedora_29.yml b/.github/workflows/fedora_29.yml
index 3f685502747a19..f3b101327f76dc 100644
--- a/.github/workflows/fedora_29.yml
+++ b/.github/workflows/fedora_29.yml
@@ -5,7 +5,7 @@ on:
   merge_group:
   push:
     branches:
-      # - master
+      - master
       - 'releases/**'
 
 concurrency:
diff --git a/.github/workflows/job_pytorch_models_tests.yml b/.github/workflows/job_pytorch_models_tests.yml
index 2959728e39dee7..d52b819981d821 100644
--- a/.github/workflows/job_pytorch_models_tests.yml
+++ b/.github/workflows/job_pytorch_models_tests.yml
@@ -22,7 +22,7 @@ permissions: read-all
 jobs:
   PyTorch_Models_Tests:
     name: PyTorch Models tests
-    timeout-minutes: ${{ inputs.model_scope == 'precommit' && 40 || 400 }}
+    timeout-minutes: ${{ inputs.model_scope == 'precommit' && 45 || 400 }}
     runs-on: ${{ inputs.runner }}
     container: ${{ fromJSON(inputs.container) }}
     defaults:
diff --git a/.github/workflows/linux_arm64.yml b/.github/workflows/linux_arm64.yml
index 0af30621a2a7fd..10de6867c7d0e2 100644
--- a/.github/workflows/linux_arm64.yml
+++ b/.github/workflows/linux_arm64.yml
@@ -5,7 +5,7 @@ on:
   merge_group:
   push:
     branches:
-      # - master
+      - master
       - 'releases/**'
 
 concurrency:
diff --git a/docs/articles_en/about-openvino/performance-benchmarks.rst b/docs/articles_en/about-openvino/performance-benchmarks.rst
index ed9d39aaf8b9e6..75d1882b8cee89 100644
--- a/docs/articles_en/about-openvino/performance-benchmarks.rst
+++ b/docs/articles_en/about-openvino/performance-benchmarks.rst
@@ -13,7 +13,7 @@ Performance Benchmarks
    Efficient LLMs for AI PC <performance-benchmarks/generative-ai-performance>
    Performance Information F.A.Q. <performance-benchmarks/performance-benchmarks-faq>
    OpenVINO Accuracy <performance-benchmarks/model-accuracy-int8-fp32>
-   Getting Performance Numbers <performance-benchmarks/getting-performance-numbers>
+   Getting Performance Numbers <performance-benchmarks/getting-performance-numbers> 
 
 
 This page presents benchmark results for the
@@ -59,12 +59,12 @@ implemented in your solutions. Click the buttons below to see the chosen benchma
    .. grid-item::
 
       .. button-link:: #
-         :class: ovms-toolkit-benchmark-llm
+         :class: ovms-toolkit-benchmark-llm-result
          :color: primary
          :outline:
          :expand:
 
-         :material-regular:`bar_chart;1.4em` OVMS for GenAI (coming soon)
+         :material-regular:`bar_chart;1.4em` OVMS for GenAI (incoming)
 
 
 
diff --git a/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json
index 0bb38199b997ca..7576fd96148554 100644
--- a/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json
+++ b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ov.json
@@ -3,7 +3,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -37,7 +37,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -71,7 +71,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -105,7 +105,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -139,7 +139,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -173,7 +173,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -207,7 +207,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -241,7 +241,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -275,7 +275,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -309,7 +309,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -343,7 +343,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -377,7 +377,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -411,7 +411,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -445,7 +445,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -479,7 +479,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -513,7 +513,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -547,7 +547,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -581,7 +581,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -615,7 +615,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -649,7 +649,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -683,7 +683,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -717,7 +717,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -751,7 +751,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -785,7 +785,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -819,7 +819,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -853,7 +853,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -887,7 +887,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1023,7 +1023,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1057,7 +1057,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1091,7 +1091,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1125,7 +1125,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1159,7 +1159,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1193,7 +1193,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1227,7 +1227,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1261,7 +1261,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1295,7 +1295,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1329,7 +1329,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1363,7 +1363,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1397,7 +1397,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1431,7 +1431,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1465,7 +1465,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1499,7 +1499,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1533,7 +1533,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1567,7 +1567,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1601,7 +1601,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1635,7 +1635,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1669,7 +1669,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1703,7 +1703,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1737,7 +1737,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1771,7 +1771,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1805,7 +1805,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1839,7 +1839,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1873,7 +1873,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1907,7 +1907,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1941,7 +1941,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -1975,7 +1975,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2009,7 +2009,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2043,7 +2043,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2077,7 +2077,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2111,7 +2111,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2145,7 +2145,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2179,7 +2179,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2213,7 +2213,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2247,7 +2247,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2281,7 +2281,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2315,7 +2315,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2349,7 +2349,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2383,7 +2383,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2417,7 +2417,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2451,7 +2451,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2485,7 +2485,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2519,7 +2519,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2553,7 +2553,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2587,7 +2587,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2621,7 +2621,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2655,7 +2655,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2689,7 +2689,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2723,7 +2723,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2859,7 +2859,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2893,7 +2893,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2927,7 +2927,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2961,7 +2961,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -2995,7 +2995,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3029,7 +3029,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3063,7 +3063,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3097,7 +3097,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3131,7 +3131,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3165,7 +3165,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3199,7 +3199,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3233,7 +3233,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3267,7 +3267,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3301,7 +3301,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3335,7 +3335,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3369,7 +3369,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3403,7 +3403,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3437,7 +3437,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3471,7 +3471,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3505,7 +3505,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3539,7 +3539,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3573,7 +3573,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3607,7 +3607,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3641,7 +3641,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3675,7 +3675,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3709,7 +3709,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3743,7 +3743,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3777,7 +3777,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3811,7 +3811,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3845,7 +3845,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3879,7 +3879,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3913,7 +3913,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3947,7 +3947,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -3981,7 +3981,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4015,7 +4015,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4049,7 +4049,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4083,7 +4083,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4117,7 +4117,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4151,7 +4151,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4185,7 +4185,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4219,7 +4219,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4253,7 +4253,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4287,7 +4287,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4321,7 +4321,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4355,7 +4355,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4389,7 +4389,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4423,7 +4423,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4457,7 +4457,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4491,7 +4491,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4525,7 +4525,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4559,7 +4559,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4593,7 +4593,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4627,7 +4627,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4661,7 +4661,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4695,7 +4695,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4729,7 +4729,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4763,7 +4763,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4899,7 +4899,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4933,7 +4933,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -4967,7 +4967,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5001,7 +5001,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5035,7 +5035,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5069,7 +5069,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5103,7 +5103,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5137,7 +5137,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5171,7 +5171,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5205,7 +5205,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5239,7 +5239,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5273,7 +5273,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5307,7 +5307,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5341,7 +5341,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5375,7 +5375,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5409,7 +5409,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5443,7 +5443,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5477,7 +5477,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5511,7 +5511,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5545,7 +5545,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5579,7 +5579,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5613,7 +5613,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5647,7 +5647,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5681,7 +5681,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5715,7 +5715,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5749,7 +5749,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5783,7 +5783,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5817,7 +5817,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5851,7 +5851,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5885,7 +5885,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5919,7 +5919,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5953,7 +5953,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -5987,7 +5987,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6021,7 +6021,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6055,7 +6055,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6089,7 +6089,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6123,7 +6123,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6157,7 +6157,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6191,7 +6191,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6225,7 +6225,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6259,7 +6259,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6293,7 +6293,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6327,7 +6327,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6361,7 +6361,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6395,7 +6395,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6429,7 +6429,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6463,7 +6463,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6497,7 +6497,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6531,7 +6531,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6565,7 +6565,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6599,7 +6599,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6633,7 +6633,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6667,7 +6667,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6701,7 +6701,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6735,7 +6735,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6769,7 +6769,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6803,7 +6803,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6939,7 +6939,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -6973,7 +6973,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7007,7 +7007,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7041,7 +7041,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7075,7 +7075,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7109,7 +7109,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7143,7 +7143,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7177,7 +7177,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7211,7 +7211,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7245,7 +7245,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7279,7 +7279,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7313,7 +7313,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7347,7 +7347,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7381,7 +7381,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7415,7 +7415,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7449,7 +7449,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7483,7 +7483,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7517,7 +7517,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7551,7 +7551,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7585,7 +7585,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7619,7 +7619,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7653,7 +7653,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7687,7 +7687,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7721,7 +7721,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7755,7 +7755,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7789,7 +7789,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7823,7 +7823,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7857,7 +7857,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7891,7 +7891,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7925,7 +7925,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7959,7 +7959,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -7993,7 +7993,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8027,7 +8027,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8061,7 +8061,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8095,7 +8095,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8129,7 +8129,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8163,7 +8163,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8197,7 +8197,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8231,7 +8231,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8265,7 +8265,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8299,7 +8299,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8333,7 +8333,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8367,7 +8367,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8401,7 +8401,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8435,7 +8435,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8469,7 +8469,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8503,7 +8503,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8537,7 +8537,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8571,7 +8571,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8605,7 +8605,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8639,7 +8639,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8775,7 +8775,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8809,7 +8809,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8843,7 +8843,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8877,7 +8877,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8911,7 +8911,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8945,7 +8945,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -8979,7 +8979,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9013,7 +9013,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9047,7 +9047,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9081,7 +9081,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9115,7 +9115,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9149,7 +9149,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9183,7 +9183,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9217,7 +9217,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9251,7 +9251,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9285,7 +9285,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9319,7 +9319,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9353,7 +9353,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9387,7 +9387,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9421,7 +9421,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9455,7 +9455,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9489,7 +9489,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9523,7 +9523,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9557,7 +9557,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9591,7 +9591,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9625,7 +9625,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9659,7 +9659,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9693,7 +9693,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9727,7 +9727,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9761,7 +9761,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9795,7 +9795,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9829,7 +9829,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9863,7 +9863,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9897,7 +9897,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9931,7 +9931,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9965,7 +9965,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -9999,7 +9999,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10033,7 +10033,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10067,7 +10067,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10101,7 +10101,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10135,7 +10135,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10169,7 +10169,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10203,7 +10203,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10237,7 +10237,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10271,7 +10271,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10305,7 +10305,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10339,7 +10339,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10373,7 +10373,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10407,7 +10407,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10441,7 +10441,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10475,7 +10475,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10509,7 +10509,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10543,7 +10543,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10577,7 +10577,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10611,7 +10611,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10645,7 +10645,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10679,7 +10679,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10713,7 +10713,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10747,7 +10747,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10781,7 +10781,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10917,7 +10917,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10951,7 +10951,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -10985,7 +10985,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11019,7 +11019,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11053,7 +11053,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11087,7 +11087,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11121,7 +11121,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11155,7 +11155,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11189,7 +11189,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11223,7 +11223,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11257,7 +11257,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11291,7 +11291,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11325,7 +11325,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11359,7 +11359,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11393,7 +11393,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11427,7 +11427,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11461,7 +11461,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11495,7 +11495,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11529,7 +11529,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11563,7 +11563,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11597,7 +11597,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11631,7 +11631,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11665,7 +11665,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11699,7 +11699,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11733,7 +11733,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11767,7 +11767,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11801,7 +11801,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11835,7 +11835,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11869,7 +11869,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11903,7 +11903,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11937,7 +11937,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -11971,7 +11971,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12005,7 +12005,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12039,7 +12039,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12073,7 +12073,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12107,7 +12107,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12141,7 +12141,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12175,7 +12175,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12209,7 +12209,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12243,7 +12243,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12277,7 +12277,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12311,7 +12311,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12345,7 +12345,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12379,7 +12379,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12413,7 +12413,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12447,7 +12447,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12481,7 +12481,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12515,7 +12515,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12549,7 +12549,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12583,7 +12583,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12617,7 +12617,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12651,7 +12651,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12685,7 +12685,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12719,7 +12719,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12753,7 +12753,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12787,7 +12787,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12821,7 +12821,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12855,7 +12855,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12889,7 +12889,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -12923,7 +12923,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13059,7 +13059,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13093,7 +13093,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13127,7 +13127,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13161,7 +13161,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13195,7 +13195,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13229,7 +13229,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13263,7 +13263,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13297,7 +13297,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13331,7 +13331,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13365,7 +13365,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13399,7 +13399,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13433,7 +13433,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13467,7 +13467,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13501,7 +13501,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13535,7 +13535,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13569,7 +13569,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13603,7 +13603,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13637,7 +13637,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13671,7 +13671,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13705,7 +13705,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13739,7 +13739,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13773,7 +13773,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13807,7 +13807,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13841,7 +13841,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13875,7 +13875,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13909,7 +13909,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13943,7 +13943,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -13977,7 +13977,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14011,7 +14011,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14045,7 +14045,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14079,7 +14079,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14113,7 +14113,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14147,7 +14147,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14181,7 +14181,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14215,7 +14215,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14249,7 +14249,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14283,7 +14283,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14317,7 +14317,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14351,7 +14351,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14385,7 +14385,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14419,7 +14419,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14453,7 +14453,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14487,7 +14487,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14521,7 +14521,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14555,7 +14555,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14589,7 +14589,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14623,7 +14623,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14657,7 +14657,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14691,7 +14691,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14725,7 +14725,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14759,7 +14759,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14793,7 +14793,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14827,7 +14827,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14861,7 +14861,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14895,7 +14895,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14929,7 +14929,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -14963,7 +14963,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15099,7 +15099,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15133,7 +15133,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15167,7 +15167,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15201,7 +15201,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15235,7 +15235,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15269,7 +15269,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15303,7 +15303,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15337,7 +15337,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15371,7 +15371,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15405,7 +15405,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15439,7 +15439,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15473,7 +15473,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15507,7 +15507,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15541,7 +15541,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15575,7 +15575,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15609,7 +15609,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15643,7 +15643,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15677,7 +15677,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15711,7 +15711,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15745,7 +15745,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15779,7 +15779,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15813,7 +15813,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15847,7 +15847,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15881,7 +15881,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15915,7 +15915,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15949,7 +15949,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -15983,7 +15983,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16017,7 +16017,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16051,7 +16051,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16085,7 +16085,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16119,7 +16119,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16153,7 +16153,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16187,7 +16187,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16221,7 +16221,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16255,7 +16255,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16289,7 +16289,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16323,7 +16323,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16357,7 +16357,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16391,7 +16391,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16425,7 +16425,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16459,7 +16459,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16493,7 +16493,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16527,7 +16527,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16561,7 +16561,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16595,7 +16595,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16629,7 +16629,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16663,7 +16663,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16697,7 +16697,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16731,7 +16731,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16765,7 +16765,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16799,7 +16799,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16833,7 +16833,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16867,7 +16867,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16901,7 +16901,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16935,7 +16935,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -16969,7 +16969,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17003,7 +17003,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17139,7 +17139,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17173,7 +17173,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17207,7 +17207,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17241,7 +17241,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17275,7 +17275,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17309,7 +17309,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17343,7 +17343,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17377,7 +17377,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17411,7 +17411,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17445,7 +17445,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17479,7 +17479,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17513,7 +17513,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17547,7 +17547,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17581,7 +17581,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17615,7 +17615,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17649,7 +17649,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17683,7 +17683,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17717,7 +17717,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17751,7 +17751,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17785,7 +17785,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17819,7 +17819,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17853,7 +17853,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17887,7 +17887,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17921,7 +17921,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17955,7 +17955,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -17989,7 +17989,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18023,7 +18023,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18057,7 +18057,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18091,7 +18091,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18125,7 +18125,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18159,7 +18159,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18193,7 +18193,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18227,7 +18227,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18261,7 +18261,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18295,7 +18295,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18329,7 +18329,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18363,7 +18363,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18397,7 +18397,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18431,7 +18431,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18465,7 +18465,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18499,7 +18499,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18533,7 +18533,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18567,7 +18567,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18601,7 +18601,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18635,7 +18635,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18669,7 +18669,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18703,7 +18703,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18737,7 +18737,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18771,7 +18771,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18805,7 +18805,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18839,7 +18839,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18873,7 +18873,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18907,7 +18907,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18941,7 +18941,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -18975,7 +18975,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19009,7 +19009,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19145,7 +19145,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19179,7 +19179,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19213,7 +19213,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19247,7 +19247,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19281,7 +19281,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19315,7 +19315,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19349,7 +19349,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19383,7 +19383,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19417,7 +19417,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19451,7 +19451,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19485,7 +19485,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19519,7 +19519,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19553,7 +19553,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19587,7 +19587,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19621,7 +19621,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19655,7 +19655,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19689,7 +19689,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19723,7 +19723,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19757,7 +19757,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19791,7 +19791,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19825,7 +19825,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19859,7 +19859,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19893,7 +19893,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19927,7 +19927,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19961,7 +19961,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -19995,7 +19995,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20029,7 +20029,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20063,7 +20063,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20097,7 +20097,7 @@
         "Platform": "Intel® Atom® x7425E CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20131,7 +20131,7 @@
         "Platform": "Intel® Atom® X6425E CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20165,7 +20165,7 @@
         "Platform": "Intel® Celeron® 6305E CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20199,7 +20199,7 @@
         "Platform": "Intel® Core™ i3-8100 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20233,7 +20233,7 @@
         "Platform": "Intel® Core™ i5-10500TE CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20267,7 +20267,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20301,7 +20301,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20335,7 +20335,7 @@
         "Platform": "Intel® Core™ i5-13600K CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20369,7 +20369,7 @@
         "Platform": "Intel® Core™ i5-8500 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20403,7 +20403,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20437,7 +20437,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20471,7 +20471,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20505,7 +20505,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20539,7 +20539,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20573,7 +20573,7 @@
         "Platform": "Intel® Core™ i7-8700T CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20607,7 +20607,7 @@
         "Platform": "Intel® Core™ i9-10900TE CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20641,7 +20641,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20675,7 +20675,7 @@
         "Platform": "Intel® Processor N100 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20709,7 +20709,7 @@
         "Platform": "Intel® Xeon® W1290P CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20743,7 +20743,7 @@
         "Platform": "Intel® Xeon® E-2124G CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20777,7 +20777,7 @@
         "Platform": "Intel® Xeon® Gold 5218T CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20811,7 +20811,7 @@
         "Platform": "Intel® Xeon® Platinum 8280 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20845,7 +20845,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20879,7 +20879,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20913,7 +20913,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20947,7 +20947,7 @@
         "Platform": "Intel® Xeon® Gold 6238L CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -20981,7 +20981,7 @@
         "Platform": "Intel® Xeon® Silver 4316 CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21015,7 +21015,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21049,7 +21049,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21083,7 +21083,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21219,7 +21219,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H NPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21253,7 +21253,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H NPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21287,7 +21287,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V NPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21321,7 +21321,7 @@
         "Platform": "Intel® Atom® x7425E iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21355,7 +21355,7 @@
         "Platform": "Intel® Atom® X6425E iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21389,7 +21389,7 @@
         "Platform": "Intel® Celeron® 6305E iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21423,7 +21423,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21457,7 +21457,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21491,7 +21491,7 @@
         "Platform": "Intel® Core™ i7-1185G7 iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21525,7 +21525,7 @@
         "Platform": "Intel® Core™ i7-1185GRE iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21559,7 +21559,7 @@
         "Platform": "Intel® Core™ i7-12700H iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21593,7 +21593,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21627,7 +21627,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21661,7 +21661,7 @@
         "Platform": "Intel® Processor N100 iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21695,7 +21695,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21729,7 +21729,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21763,7 +21763,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21797,7 +21797,7 @@
         "Platform": "Intel® Atom® x7425E CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21831,7 +21831,7 @@
         "Platform": "Intel® Atom® X6425E CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21865,7 +21865,7 @@
         "Platform": "Intel® Celeron® 6305E CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21899,7 +21899,7 @@
         "Platform": "Intel® Core™ i5-1235U Processor CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21933,7 +21933,7 @@
         "Platform": "Intel® Core™ i5-1335U Processor CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -21967,7 +21967,7 @@
         "Platform": "Intel® Core™ i7-1185G7 CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22001,7 +22001,7 @@
         "Platform": "Intel® Core™ i7-1185GRE CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22035,7 +22035,7 @@
         "Platform": "Intel® Core™ i7-12700H CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22069,7 +22069,7 @@
         "Platform": "Intel® Core™ i7-1355U Processor CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22103,7 +22103,7 @@
         "Platform": "Intel® Core™ i7-1360P CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22137,7 +22137,7 @@
         "Platform": "Intel® Processor N100 CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Mobile Platforms (Intel® Atom™)",
+        "PlatformType": "Intel® Atom™, CPU+iGPU",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22171,7 +22171,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 155H CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22205,7 +22205,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22239,7 +22239,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22273,7 +22273,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22307,7 +22307,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22341,7 +22341,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22375,7 +22375,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22511,7 +22511,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22545,7 +22545,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22579,7 +22579,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22613,7 +22613,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22647,7 +22647,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22681,7 +22681,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22715,7 +22715,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22749,7 +22749,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22885,7 +22885,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22919,7 +22919,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22953,7 +22953,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -22987,7 +22987,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23021,7 +23021,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23055,7 +23055,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23089,7 +23089,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23123,7 +23123,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23225,7 +23225,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23259,7 +23259,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23293,7 +23293,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23327,7 +23327,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23361,7 +23361,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23395,7 +23395,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23429,7 +23429,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23463,7 +23463,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23599,7 +23599,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23633,7 +23633,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23667,7 +23667,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23701,7 +23701,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23735,7 +23735,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23769,7 +23769,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23803,7 +23803,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23837,7 +23837,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -23973,7 +23973,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24007,7 +24007,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24041,7 +24041,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24075,7 +24075,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24109,7 +24109,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24143,7 +24143,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24177,7 +24177,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24211,7 +24211,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H CPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24347,7 +24347,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24381,7 +24381,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 165H iGPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24415,7 +24415,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24449,7 +24449,7 @@
         "Platform": "Intel® Core™ i9-13900K CPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24483,7 +24483,7 @@
         "Platform": "Intel® Xeon® Platinum 8380 CPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24517,7 +24517,7 @@
         "Platform": "Intel® Xeon® Platinum 8480+ CPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24551,7 +24551,7 @@
         "Platform": "Intel® Xeon® Platinum 8580 CPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Server Platforms (Intel® Xeon®)",
+        "PlatformType": "Intel® Xeon®, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24653,7 +24653,7 @@
         "Platform": "Intel® Core™ i7-1360P iGPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24687,7 +24687,7 @@
         "Platform": "Intel® Core™ Ultra 9 processor 288V iGPU-only",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24721,7 +24721,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24753,9 +24753,9 @@
     },
     {
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
-        "Model": "bert-large-uncased",
+        "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24789,7 +24789,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24823,7 +24823,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24857,7 +24857,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24891,7 +24891,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24925,7 +24925,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24959,7 +24959,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -24993,7 +24993,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25027,7 +25027,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25061,7 +25061,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU-only",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, CPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25095,7 +25095,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25127,9 +25127,9 @@
     },
     {
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
-        "Model": "bert-large-uncased",
+        "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25163,7 +25163,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25197,7 +25197,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25231,7 +25231,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25265,7 +25265,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25299,7 +25299,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25333,7 +25333,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25367,7 +25367,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25401,7 +25401,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25435,7 +25435,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25469,7 +25469,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25501,9 +25501,9 @@
     },
     {
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
-        "Model": "bert-large-uncased",
+        "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25537,7 +25537,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25571,7 +25571,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25605,7 +25605,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25639,7 +25639,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25673,7 +25673,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25707,7 +25707,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25741,7 +25741,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25775,7 +25775,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25809,7 +25809,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V CPU+iGPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25843,7 +25843,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "bert-base-cased",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25875,9 +25875,9 @@
     },
     {
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
-        "Model": "bert-large-uncased",
+        "Model": "bert-large-uncased-whole-word-masking-squad-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25911,7 +25911,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "efficientdet-d0",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25945,7 +25945,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "mask_rcnn_resnet50_atrous_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -25979,7 +25979,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "mobilenet-v2",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26013,7 +26013,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "resnet-50",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26047,7 +26047,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "ssd_mobilenet_v1_coco",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26081,7 +26081,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "ssd-resnet34-1200",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26115,7 +26115,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "unet-camvid-onnx-0001",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26149,7 +26149,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "yolo_v5m",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26183,7 +26183,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V NPU",
         "Model": "yolo_v8n",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, NPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26217,7 +26217,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "chatglm2-6b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26251,7 +26251,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "falcon-7b-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26283,9 +26283,9 @@
     },
     {
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
-        "Model": "llama-2-7b-chat-hf",
+        "Model": "llama-2-7b-chat",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26319,7 +26319,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "llama-3-8b",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26353,7 +26353,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "mistral-7b-v0.1",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26387,7 +26387,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "phi-3-mini-4k-instruct",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
@@ -26421,7 +26421,7 @@
         "Platform": "Intel® Core™ Ultra 7 processor 268V iGPU",
         "Model": "stable-diffusion-v1-5",
         "Checked": "true",
-        "PlatformType": "Client Platforms (Intel® Core™)",
+        "PlatformType": "Intel® Core™, iGPU-only",
         "Parameters": {
             "throughput": {
                 "Precisions": [
diff --git a/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ovms-genai.json b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ovms-genai.json
new file mode 100644
index 00000000000000..f96fb11e6b029d
--- /dev/null
+++ b/docs/sphinx_setup/_static/benchmarks_files/data/graph-data-ovms-genai.json
@@ -0,0 +1,96 @@
+[
+    {
+        "Platform": "Intel® Xeon® Platinum 8580",
+        "Model": "mistralai/Mistral-7B-v0.1",
+        "PlatformType": "None",
+        "Parameters": {
+            "Vllm": {
+                "Precisions": [
+                    {
+                        "Throughput": {
+                            "0.2": "350.06",
+                            "0.6": "486.89",
+                            "0.8": "575.92",
+                            "2.0": "778.07"
+                        }
+                    },
+                    {
+                        "Latency": {
+                            "0.2": "60.93",
+                            "0.6": "91.63",
+                            "0.8": "113.61",
+                            "2.0": "240.25"
+                        }
+                    }
+                ]
+            },
+            "Ovms": {
+                "Precisions": [
+                    {
+                        "Throughput": {
+                            "0.2": "90.98",
+                            "0.6": "266.24",
+                            "0.8": "351.63",
+                            "2.0": "195.16"
+                        }
+                    },
+                    {
+                        "Latency": {
+                            "0.2": "54.9",
+                            "0.6": "78.78",
+                            "0.8": "95.78",
+                            "2.0": "352.23"
+                        }
+                    }
+                ]
+            }
+        }
+    },
+    {
+        "Platform": "Intel® Xeon® Platinum 8530",
+        "Model": "mistralai/Mistral-7B-v0.1",
+        "PlatformType": "None",
+        "Parameters": {
+            "Vllm": {
+                "Precisions": [
+                    {
+                        "Throughput": {
+                            "0.2": "350.06",
+                            "0.6": "486.89",
+                            "0.8": "575.92",
+                            "2.0": "778.07"
+                        }
+                    },
+                    {
+                        "Latency": {
+                            "0.2": "60.93",
+                            "0.6": "91.63",
+                            "0.8": "113.61",
+                            "2.0": "240.25"
+                        }
+                    }
+                ]
+            },
+            "Ovms": {
+                "Precisions": [
+                    {
+                        "Throughput": {
+                            "0.2": "90.98",
+                            "0.6": "266.24",
+                            "0.8": "351.63",
+                            "2.0": "195.16"
+                        }
+                    },
+                    {
+                        "Latency": {
+                            "0.2": "54.9",
+                            "0.6": "78.78",
+                            "0.8": "95.78",
+                            "2.0": "352.23"
+                        }
+                    }
+                ]
+            }
+        }
+    }
+]
\ No newline at end of file
diff --git a/docs/sphinx_setup/_static/benchmarks_files/graph-config.json b/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
index 6fb8d19e1a1adf..29fbe714094b74 100644
--- a/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
+++ b/docs/sphinx_setup/_static/benchmarks_files/graph-config.json
@@ -1,4 +1,3 @@
-
 {
     "PrecisionsMap": {
         "INT4": "int4",
@@ -9,7 +8,9 @@
         "FP32_OV": "fp32_ov",
         "FP32_OVMS": "fp32_ovms",
         "INT8_OV": "int8_ov",
-        "INT8_OVMS": "int8_ovms"
+        "INT8_OVMS": "int8_ovms",
+        "THROUGHPUT": "Throughput",
+        "LATENCY": "Latency"
     },
     "ParametersMap": {
         "Throughput": "throughput",
@@ -71,6 +72,30 @@
             "data": null,
             "color": "#00536a",
             "label": "INT8 OVMS"
+        },
+        "Vllm": {
+            "Latency": {
+                "data": null,
+                "color": "#FDB2BC",
+                "label": "Latency"
+            },
+            "Throughput": {
+                "data": null,
+                "color": "#91CDF7",
+                "label": "Throughput"
+            }
+        },
+        "Ovms": {
+            "Latency": {
+                "data": null,
+                "color": "#CDB2BC",
+                "label": "Latency"
+            },
+            "Throughput": {
+                "data": null,
+                "color": "#12CDF7",
+                "label": "Throughput"
+            }
         }
     },
     "Filters": [
@@ -80,13 +105,16 @@
         "platformTypes": {
             "name": "ietype",
             "data": [
-                "Client Platforms (Intel® Core™)"
+                "None",
+                "Intel® Core™, CPU-only",
+                "Intel® Core™, iGPU-only",
+                "Intel® Core™, NPU-only",
+                "Intel® Core™, CPU+iGPU"
             ]
         },
         "platforms": {
             "name": "platform",
-            "data": [
-            ]
+            "data": []
         },
         "platformFilters": {
             "name": "coretype",
@@ -97,21 +125,24 @@
         "models": {
             "name": "networkmodel",
             "data": [
-                "bert-base-cased"
+                "bert-base-cased",
+                "resnet-50",
+                "yolo_v8n",
+                "llama-3-8B"
             ]
         },
         "parameters": {
             "name": "parameters",
             "data": [
-                "Throughput",
-                "Latency"
+                "Vllm",
+                "Ovms"
             ]
         },
         "precision": {
             "name": "precision",
             "data": [
-                "INT4",
-                "INT8"
+                "THROUGHPUT",
+                "LATENCY"
             ]
         }
     }
diff --git a/docs/sphinx_setup/_static/download/supported_models.csv b/docs/sphinx_setup/_static/download/supported_models.csv
index 1c7db3ab6bfc9d..87ea37b0f207c3 100644
--- a/docs/sphinx_setup/_static/download/supported_models.csv
+++ b/docs/sphinx_setup/_static/download/supported_models.csv
@@ -344,8 +344,7 @@ mask_rcnn_resnet101_atrous_coco,Instance Segmentation,tf,FP16-INT8,+,+,
 mask_rcnn_resnet50_atrous_coco,Instance Segmentation,tf,FP16,+,+,
 mask_rcnn_resnet50_atrous_coco,Instance Segmentation,tf,FP16-INT8,+,+,
 mask_rcnn_resnet50_atrous_coco,Instance Segmentation,tf,FP32,+,+,
-MaskRCNN-12,Object Detection,onnx,FP16,,,+
-MaskRCNN-12,Object Detection,onnx,FP32,+,+,+
+MaskRCNN-12,Object Detection,onnx,FP32,+,+,
 mbart-large-50-many-to-one-mmt,Natural Language Processing,pytorch,intel-optimum default,,+,
 Meta-Llama-3-8B,Large Language Model,pytorch,intel-optimum default,,+,
 Meta-Llama-3-8B-Instruct,Large Language Model,pytorch,intel-optimum default,,+,
diff --git a/docs/sphinx_setup/_static/html/modalLLM.html b/docs/sphinx_setup/_static/html/modalLLM.html
new file mode 100644
index 00000000000000..e3395a16931188
--- /dev/null
+++ b/docs/sphinx_setup/_static/html/modalLLM.html
@@ -0,0 +1,95 @@
+<div>
+    <div class="modal-header">
+        <h2>Benchmark Graph Builder</h2>
+        <span class="modal-close">&times;</span>
+    </div>
+    <div class="modal-line-divider"></div>
+    <section id="modal-configure-graphs" class="modal-configure-graphs">
+        <div id="configure-graphs-header" class="configure-graphs-header">
+            <h3>Configure Graphs</h3>
+            <div class="buttons-nav">
+                <div>
+                    <button id="build-graphs-btn" disabled="disabled" class="build-graphs-btn">Show Graphs</button>
+                </div>
+                <div class="clear-all-btn">
+                    <span class="clear-all-btn-content">Clear All</span>
+                </div>
+            </div>
+        </div>
+        <div class="configure-graphs-content">
+            <div class="modal-content-grid-container">
+                <div class="modal-content-grid-item">
+                    <div title="Select\deselect all network model list" class="show-allcheckbox">
+                        <span class="models-selectall">
+                        </span>
+                    </div>
+                    <h5>Models</h5>
+                    <div class="modal-line-divider"></div>
+                    <div class="modal-content-grid">
+                        <div class="models-column column"></div>
+                    </div>
+                </div>
+                <div class="modal-content-grid-item">
+                    <div title="Select\deselect all platform list" class="show-allcheckbox">
+                        <span class="platforms-selectall">
+                        </span>
+                    </div>
+                    <h5>Platforms</h5>
+                    <div id="filters" title="Filter the platform list" class="show-filter">
+                        <span class="filters-label">Show filters</span>
+                        <span class="show-filters-icon"></span>
+                    </div>
+                    <div class="modal-line-divider"></div>
+                    <div class="modal-content-grid">
+                        <div class="platforms-column column"></div>
+                    </div>
+                </div>
+                <div class="modal-content-grid-item">
+                    <h5>Engines</h5>
+                    <div class="modal-line-divider"></div>
+                    <div class="modal-content-grid">
+                        <div class="kpi-column column"></div>
+                    </div>
+                    <h5>Parameters</h5>
+                    <div class="modal-line-divider"></div>
+                    <div class="modal-content-grid">
+                        <div class="precisions-column column"></div>
+                    </div>
+                </div>
+            </div>
+        </div>
+        <div class="configure-graphs-content">
+            <div class="modal-content-grid-container">
+                <div id="modal-filters" class="modal-filter">
+                    <div class="modal-filters-content">
+                        <div class="modal-header">
+                            <h2>Show\hide platform types</h2>
+                            <span class="close-filters"><span class="arrow-back-icon"></span></span>
+                        </div>
+                        <div class="show-allcheckbox">
+                            <span class="ietype-selectall"></span>
+                        </div>
+                        <h5>Platform Types</h5>
+                        <div class="modal-line-divider"></div>
+                        <div class="modal-content-grid">
+                            <div class="ietype-column column"></div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </section>
+    <section id="modal-display-graphs" class="modal-display-graphs">
+        <div class="benchmark-graph-results-header">
+            <h3>Graph Results</h3>
+            <div class="edit-settings-btn">
+                <div class="edit-settings-text">Edit Settings
+                    <span class="edit-settings-icon"></span>
+                </div>
+            </div>
+        </div>
+        <div class="chart-placeholder"></div>
+    </section>
+    <div class="modal-footer">
+    </div>
+</div>
\ No newline at end of file
diff --git a/docs/sphinx_setup/_static/js/graphs.js b/docs/sphinx_setup/_static/js/graphs.js
index f8146c1580c58e..4d621ce0780261 100644
--- a/docs/sphinx_setup/_static/js/graphs.js
+++ b/docs/sphinx_setup/_static/js/graphs.js
@@ -1,173 +1,4 @@
-// =================== GENERAL OUTPUT CONFIG =========================
-
-class Filter {
-
-    // param: GraphData[], networkModels[]
-    static FilterByNetworkModel(graphDataArr, networkModels) {
-        const optionMap = new Map();
-        networkModels.map((model) => graphDataArr.filter((graphData => graphData.Model === model)))
-            .flat(1)
-            .forEach(item => optionMap.set(item.Platform, item));
-        return Array.from(optionMap.values());
-    }
-
-    // param: GraphData[], ieType
-    static ByIeTypes(graphDataArr, ieTypes) {
-        const optionMap = new Map();
-        graphDataArr
-            .filter(graphData => ieTypes.includes(graphData.PlatformType))
-            .forEach(item => optionMap.set(item.Platform, item));
-        return Array.from(optionMap.values());
-    }
-
-    // param: GraphData[], ieType, networkModels
-    static ByTypesAndModels(graphDataArr, ieTypes, models) {
-        const optionMap = new Map();
-        graphDataArr
-            .filter(graphData => ieTypes.includes(graphData.PlatformType))
-            .filter(graphData => models.includes(graphData.Model))
-            .forEach(item => optionMap.set(item.Platform, item));
-        return Array.from(optionMap.values());
-    }
-
-    // param: GraphData[], clientPlatforms
-    static ByIeKpis(graphDataArr, clientPlatforms) {
-        var kpis = []
-        clientPlatforms.forEach((platformName) => {
-            graphDataArr.filter((data) => {
-                if (data.Platform.includes(platformName)) {
-                    for (var key in data.Parameters) {
-                        if (!kpis.includes(key)) kpis.push(key)
-                    }
-                }
-            })
-        })
-        return kpis;
-    }
-
-    // param: GraphData[]
-    static getParameters(graphDataArr) {
-        var parameters = []
-        graphDataArr.filter((data) => {
-            for (var key in data.Parameters) {
-                if (!parameters.includes(Graph.capitalizeFirstLetter(key))) parameters.push(Graph.capitalizeFirstLetter(key))
-            }
-        })
-        return parameters;
-    }
-
-    // param: GraphData[]
-    static getIeTypes(graphDataArr) {
-        var kpis = []
-        graphDataArr.filter((data) => {
-            for (var key in data.Parameters) {
-                if (!kpis.includes(Graph.capitalizeFirstLetter(key))) kpis.push(Graph.capitalizeFirstLetter(key))
-            }
-        })
-        return kpis;
-    }
-
-    // param: GraphData[], clientPlatforms[]
-    static ByClientPlatforms(graphDataArr, platformsArr) {
-        return graphDataArr.filter((data) => {
-            return platformsArr.includes(data.Platform)
-        });
-    }
-
-    // param: GraphData[], coreTypes[]
-    static FilterByCoreTypes(graphDataArr, coreTypes) {
-        if (coreTypes) {
-            return graphDataArr.filter((data) => coreTypes.includes(data.PlatformType));
-        }
-        return graphDataArr;
-    }
-}
-
-class Modal {
-    static getPrecisionsLabels(graphDataArr) {
-        var kpis = []
-        graphDataArr.filter((data) => {
-            for (var key in data.Parameters) {
-                data.Parameters[key].Precisions.forEach((key) => {
-                    Object.keys(key).forEach((key) => {
-                        if (!kpis.includes(key.toUpperCase())) kpis.push(key.toUpperCase())
-                    });
-                })
-            }
-        })
-        return kpis;
-    }
-
-    static getPrecisions(appConfig, labels) {
-        return labels.map((label) => {
-            var prec = appConfig.PrecisionsMap[label];
-            if (prec !== undefined) {
-                return prec;
-            }
-            else {
-                return "no name";
-            }
-        });
-    }
-}
-
-
-class Graph {
-    // functions to get unique keys 
-    static getNetworkModels(graphDataArr) {
-        return Array.from(new Set(graphDataArr.map((obj) => obj.Model)));
-    }
-    static getIeTypes(graphDataArr) {
-        return Array.from(new Set(graphDataArr.map((obj) => obj.PlatformType)));
-    }
-    static getCoreTypes(graphDataArr) {
-        return Array.from(new Set(graphDataArr.map((obj) => obj.ieType)));
-    }
-
-    // param: GraphData[]
-    static getPlatformNames(graphDataArr) {
-        return graphDataArr.map((data) => data.Platform);
-    }
-
-    // param: GraphData[], parameterName: string, precisions: list
-    static getDatabyParameter(graphDataArr, parameterName, precisions) {
-        var array = [];
-        graphDataArr.forEach((item) => {
-            if (item.Parameters[parameterName] !== undefined) {
-                array.push(item.Parameters[parameterName].Precisions);
-            }
-            else {
-                var obj = {};
-                precisions.forEach((prec) => {
-                    obj[prec] = 0;
-                })
-                array.push([obj])
-            }
-        })
-        return array;
-
-    }
-
-    // this returns an object that is used to ender the chart
-    static getGraphConfig(parameterName, item, precisions, appConfig) {
-        return {
-            chartTitle: Graph.capitalizeFirstLetter(parameterName),
-            iconClass: parameterName + '-icon',
-            unit: item.Parameters[parameterName]?.Unit,
-            datasets: precisions.map((precision) => appConfig.PrecisionData[precision]),
-        };
-    }
-    static capitalizeFirstLetter(string) {
-        return string.charAt(0).toUpperCase() + string.slice(1);
-    }
-}
-
-class ChartDisplay {
-    constructor(mode, numberOfCharts) {
-        this.mode = mode;
-        this.numberOfChartsInRow = numberOfCharts;
-    }
-}
+// =================== ADDITIONAL OUTPUT CONFIG =========================
 
 $(document).ready(function () {
 
@@ -186,7 +17,6 @@ $(document).ready(function () {
 
         $('.graph-chart-title-header').off('click').on('click', (event) => {
             var parent = event.target.parentElement;
-
             if ($(parent).children('.chart-wrap,.empty-chart-container').is(":visible")) {
                 $(parent).children('.chart-wrap,.empty-chart-container').hide();
                 $(parent).children('.chevron-right-btn').show();
@@ -702,11 +532,10 @@ $(document).ready(function () {
         chartContainer.append(chartWrap);
         var graphConfigs = parameters.map((parameter) => {
             var groupUnit = model[0];
-            var kpiData = Graph.getDatabyParameter(model, appConfig.ParametersMap[parameter], precisions);
-            var config = Graph.getGraphConfig(appConfig.ParametersMap[parameter], groupUnit, precisions, JSON.parse(JSON.stringify(appConfig)));
+            var kpiData = Graph.getDatabyParameterOld(model, appConfig.ParametersMap[parameter], precisions);
+            var config = Graph.getGraphConfigOld(appConfig.ParametersMap[parameter], groupUnit, precisions, JSON.parse(JSON.stringify(appConfig)));
             precisions.forEach((precision, index) => {
-                config.datasets[index].data = kpiData.map(tData => tData[0][precision]
-                );
+                config.datasets[index].data = kpiData.map(tData => tData[0][precision]);
             });
             return config;
         });
diff --git a/docs/sphinx_setup/_static/js/graphsLLM.js b/docs/sphinx_setup/_static/js/graphsLLM.js
new file mode 100644
index 00000000000000..4dbc0313e2a133
--- /dev/null
+++ b/docs/sphinx_setup/_static/js/graphsLLM.js
@@ -0,0 +1,889 @@
+// =================== GENERAL OUTPUT CONFIG =========================
+
+class Filter {
+
+    // param: GraphData[], networkModels[]
+    static FilterByNetworkModel(graphDataArr, networkModels) {
+        const optionMap = new Map();
+        networkModels.map((model) => graphDataArr.filter((graphData => graphData.Model === model)))
+            .flat(1)
+            .forEach(item => optionMap.set(item.Platform, item));
+        return Array.from(optionMap.values());
+    }
+
+    // param: GraphData[], ieType
+    static ByIeTypes(graphDataArr, ieTypes) {
+        const optionMap = new Map();
+        graphDataArr
+            .filter(graphData => ieTypes.includes(graphData.PlatformType))
+            .forEach(item => optionMap.set(item.Platform, item));
+        return Array.from(optionMap.values());
+    }
+
+    // param: GraphData[], ieType, networkModels
+    static ByTypesAndModels(graphDataArr, ieTypes, models) {
+        const optionMap = new Map();
+        graphDataArr
+            .filter(graphData => ieTypes.includes(graphData.PlatformType))
+            .filter(graphData => models.includes(graphData.Model))
+            .forEach(item => optionMap.set(item.Platform, item));
+        return Array.from(optionMap.values());
+    }
+
+    // param: GraphData[], clientPlatforms
+    static ByIeKpis(graphDataArr, clientPlatforms) {
+        var kpis = []
+        clientPlatforms.forEach((platformName) => {
+            graphDataArr.filter((data) => {
+                if (data.Platform.includes(platformName)) {
+                    for (var key in data.Parameters) {
+                        if (!kpis.includes(key)) kpis.push(key)
+                    }
+                }
+            })
+        })
+        return kpis;
+    }
+
+    // param: GraphData[]
+    static getParameters(graphDataArr) {
+        var parameters = []
+        graphDataArr.filter((data) => {
+            for (var key in data.Parameters) {
+                if (!parameters.includes(Graph.capitalizeFirstLetter(key))) parameters.push(Graph.capitalizeFirstLetter(key))
+            }
+        })
+        return parameters;
+    }
+
+    // param: GraphData[]
+    static getIeTypes(graphDataArr) {
+        var kpis = []
+        graphDataArr.filter((data) => {
+            for (var key in data.Parameters) {
+                if (!kpis.includes(Graph.capitalizeFirstLetter(key))) kpis.push(Graph.capitalizeFirstLetter(key))
+            }
+        })
+        return kpis;
+    }
+
+    // param: GraphData[], clientPlatforms[]
+    static ByClientPlatforms(graphDataArr, platformsArr) {
+        return graphDataArr.filter((data) => {
+            return platformsArr.includes(data.Platform)
+        });
+    }
+
+    // param: GraphData[], coreTypes[]
+    static FilterByCoreTypes(graphDataArr, coreTypes) {
+        if (coreTypes) {
+            return graphDataArr.filter((data) => coreTypes.includes(data.PlatformType));
+        }
+        return graphDataArr;
+    }
+}
+
+class Modal {
+    static getPrecisionsLabels(graphDataArr) {
+        var kpis = []
+        graphDataArr.filter((data) => {
+            for (var key in data.Parameters) {
+                data.Parameters[key].Precisions.forEach((key) => {
+                    Object.keys(key).forEach((key) => {
+                        if (!kpis.includes(key.toUpperCase())) kpis.push(key.toUpperCase())
+                    });
+                })
+            }
+        })
+        return kpis;
+    }
+
+    static getPrecisions(appConfig, labels) {
+        return labels.map((label) => {
+            var prec = appConfig.PrecisionsMap[label];
+            if (prec !== undefined) {
+                return prec;
+            }
+            else {
+                return "no name";
+            }
+        });
+    }
+}
+
+class Graph {
+    // functions to get unique keys 
+    static getNetworkModels(graphDataArr) {
+        return Array.from(new Set(graphDataArr.map((obj) => obj.Model)));
+    }
+    static getIeTypes(graphDataArr) {
+        return Array.from(new Set(graphDataArr.map((obj) => obj.PlatformType)));
+    }
+    static getCoreTypes(graphDataArr) {
+        return Array.from(new Set(graphDataArr.map((obj) => obj.ieType)));
+    }
+
+    // param: GraphData[]
+    static getPlatformNames(graphDataArr) {
+        return graphDataArr.map((data) => data.Platform);
+    }
+
+    // param: GraphData[], engine: string, precisions: list
+    static getDatabyParameter(graphDataArr, engine, array) {
+        if (!Array.isArray(array[engine])) {
+            array[engine] = [];
+        }
+        array[engine].push(graphDataArr.Parameters[engine].Precisions);
+        return array;
+    }
+
+    // this returns an object that is used to ender the chart
+    static getGraphConfig(engine, precisions, appConfig) {
+        return {
+            chartTitle: 'Throughput vs Latency',
+            iconClass: 'latency-icon',
+            datasets: precisions.map((precision) => appConfig.PrecisionData[engine][precision]),
+            unit: "None"
+        };
+    }
+    // param: GraphData[], parameterName: string, precisions: list
+    static getDatabyParameterOld(graphDataArr, parameterName, precisions) {
+        var array = [];
+        graphDataArr.forEach((item) => {
+            if (item.Parameters[parameterName] !== undefined) {
+                array.push(item.Parameters[parameterName].Precisions);
+            }
+            else {
+                var obj = {};
+                precisions.forEach((prec) => {
+                    obj[prec] = 0;
+                })
+                array.push([obj])
+            }
+        })
+        return array;
+
+    }
+
+    // this returns an object that is used to ender the chart
+    static getGraphConfigOld(parameterName, item, precisions, appConfig) {
+        return {
+            chartTitle: Graph.capitalizeFirstLetter(parameterName),
+            iconClass: parameterName + '-icon',
+            unit: item.Parameters[parameterName]?.Unit,
+            datasets: precisions.map((precision) => appConfig.PrecisionData[precision]),
+        };
+    }
+    static capitalizeFirstLetter(string) {
+        return string.charAt(0).toUpperCase() + string.slice(1);
+    }
+}
+
+class ChartDisplay {
+    constructor(mode, numberOfCharts) {
+        this.mode = mode;
+        this.numberOfChartsInRow = numberOfCharts;
+    }
+}
+
+$(document).ready(function () {
+    $('.ovms-toolkit-benchmark-llm-result').on('click', () => showModal("graph-data-ovms-genai.json"));
+    function clickBuildGraphsLLM(graph, appConfig, networkModels, ieTypes, platforms, kpis, precisions) {
+        renderData(graph, appConfig, networkModels, ieTypes, platforms, kpis, precisions);
+        $('.modal-footer').show();
+        $('#modal-display-graphs').show();
+        $('.edit-settings-btn').off('click').on('click', (event) => {
+            $('#modal-configure-graphs').show();
+            $('#modal-display-graphs').hide();
+            $('.modal-footer').hide();
+            $('.chart-placeholder').empty();
+        });
+
+        $('.graph-chart-title-header').off('click').on('click', (event) => {
+            var parent = event.target.parentElement;
+
+            if ($(parent).children('.chart-wrap,.empty-chart-container').is(":visible")) {
+                $(parent).children('.chart-wrap,.empty-chart-container').hide();
+                $(parent).children('.chevron-right-btn').show();
+                $(parent).children('.chevron-down-btn').hide();
+            } else {
+                $(parent).children('.chart-wrap,.empty-chart-container').show();
+                $(parent).children('.chevron-down-btn').show();
+                $(parent).children('.chevron-right-btn').hide();
+            }
+        });
+    }
+
+    function hideModal() {
+        $('#graphModal').remove();
+        $('body').css('overflow', 'auto');
+    }
+
+    function showModal(file) {
+        $('body').css('overflow', 'hidden');
+
+        fetch('../_static/benchmarks_files/data/' + file)
+            .then((response) => response.json())
+            .then((jsonData) => {
+                fetch('../_static/benchmarks_files/graph-config.json')
+                    .then((configResponse) => configResponse.json())
+                    .then((appConfig) => {
+                        renderModal(jsonData, appConfig)
+                    })
+            });
+    }
+
+    function getSelectedNetworkModels() {
+        return $('.models-column input:checked, .platforms-column input:checked').not('[data-networkmodel="Select All"]').map(function () {
+            return $(this).data('networkmodel');
+        }).get();
+    }
+
+    function getSelectedIeTypes() {
+        return $('.ietype-column input:checked').map(function () {
+            return $(this).data('ietype');
+        }).get();
+    }
+
+    function getSelectedClientPlatforms() {
+        return $('.platforms-column input:checked').map(function () {
+            return $(this).data('platform');
+        }).get();
+    }
+
+    function getSelectedKpis() {
+        return $('.kpi-column input:checked').map(function () {
+            return $(this).data('kpi');
+        }).get();
+    }
+
+    function getSelectedPrecisions() {
+        return $('.precisions-column input:checked').map(function () {
+            return $(this).data('precision');
+        }).get();
+    }
+
+    function validateSelections() {
+        if (getSelectedNetworkModels().length > 0
+            && getSelectedIeTypes()
+            && getSelectedClientPlatforms().length > 0
+            && getSelectedKpis().length > 0) {
+            if (getSelectedPrecisions().length > 0) {
+                $('#build-graphs-btn').prop('disabled', false);
+                return;
+            }
+            $('#build-graphs-btn').prop('disabled', true);
+            return;
+        }
+        $('#build-graphs-btn').prop('disabled', true);
+    }
+
+    function renderModal(graph, appConfig) {
+        new Graph(graph);
+        var networkModels = Graph.getNetworkModels(graph);
+        var ieTypes = Graph.getIeTypes(graph);
+        fetch('../_static/html/modalLLM.html').then((response) => response.text()).then((text) => {
+
+            // generate and configure modal container
+            var modal = $('<div>');
+            modal.attr('id', 'graphModal');
+            modal.addClass('modal');
+            var modalContent = $(text);
+            modalContent.attr('id', 'graphModalContent');
+            modalContent.addClass('modal-content');
+            modal.append(modalContent);
+
+            const models = networkModels.map((networkModel) => createCheckMark(networkModel, 'networkmodel'));
+            modal.find('.models-column').append(models);
+
+            const selectAllModelsButton = createCheckMark('', 'networkmodel');
+            modal.find('.models-selectall').append(selectAllModelsButton);
+
+            const selectAllPlatformsButton = createCheckMark('', 'platform');
+            modal.find('.platforms-selectall').append(selectAllPlatformsButton);
+
+            const precisions = Modal.getPrecisionsLabels(graph).map((precision) => createCheckMark(precision, 'precision', false));
+            modal.find('.precisions-column').append(precisions);
+
+            selectAllCheckboxes(precisions);
+            disableAllCheckboxes(precisions);
+
+            const selectAllTypesButton = createCheckMark('', 'ietype')
+            modal.find('.ietype-selectall').append(selectAllTypesButton);
+
+            const iefilter = ieTypes.map((ieType) => createCheckMark(ieType, 'ietype'));
+            modal.find('.ietype-column').append(iefilter);
+
+            modal.find('#modal-display-graphs').hide();
+            modal.find('.ietype-column input').first().prop('checked', true);
+
+            const kpiLabels = Filter.getParameters(graph).map((parameter) => createCheckMark(parameter, 'kpi', false));
+            modal.find('.kpi-column').append(kpiLabels);
+
+            $('body').prepend(modal);
+
+            preselectDefaultSettings(graph, modal, appConfig);
+
+            //is not generic solution :(
+            if (appConfig.DefaultSelections.platformTypes?.data?.includes('Select All')) {
+                selectAllCheckboxes(iefilter);
+
+            };
+            renderClientPlatforms(graph, modal);
+
+            $('.clear-all-btn').on('click', clearAll);
+            $('#build-graphs-btn').on('click', () => {
+                $('#modal-configure-graphs').hide();
+                clickBuildGraphsLLM(graph, appConfig, getSelectedNetworkModels(), getSelectedIeTypes(), getSelectedClientPlatforms(), getSelectedKpis(), Modal.getPrecisions(appConfig, getSelectedPrecisions()));
+            });
+            $('.modal-close').on('click', hideModal);
+            $('.close-btn').on('click', hideModal);
+
+            modal.find('.ietype-selectall input').on('click', function () {
+                if ($(this).prop('checked'))
+                    selectAllCheckboxes(iefilter);
+                else deSelectAllCheckboxes(iefilter);
+            });
+
+            modal.find('.models-selectall input').on('click', function () {
+                if ($(this).prop('checked')) selectAllCheckboxes(models);
+                else deSelectAllCheckboxes(models);
+
+                renderClientPlatforms(graph, modal)
+            });
+
+            modal.find('.platforms-selectall input').on('click', function () {
+                if ($(this).prop('checked'))
+                    renderClientPlatforms(graph, modal)
+                else {
+                    var enabledPlatforms = modal.find('.platforms-column .checkmark-container');
+                    deSelectCheckbox(enabledPlatforms);
+                };
+
+            });
+
+            modal.find('.models-column input').on('click', function () {
+                if (!$(this)[0].checked) {
+                    deSelectCheckbox(selectAllModelsButton);
+                }
+            });
+
+
+            modal.find('.ietype-column input').on('click', function () {
+                if (!$(this)[0].checked) {
+                    deSelectCheckbox(selectAllTypesButton);
+                }
+            });
+
+            modal.find('.models-column input').on('click', () => renderClientPlatforms(graph, modal));
+            modal.find('.ietype-column input').on('click', () => renderClientPlatforms(graph, modal));
+            modal.find('.ietype-selectall input').on('click', () => renderClientPlatforms(graph, modal));
+            modal.find('.platforms-column').on('click', () => enableParmeters(graph, getSelectedClientPlatforms()));
+
+            modal.find('.kpi-column input').on('click', validatePrecisionSelection);
+            modal.find('input').on('click', validateSelections);
+
+            var modalFilters = document.getElementById("modal-filters");
+
+            var showFiltersButton = document.getElementById("filters");
+            showFiltersButton.onclick = function () {
+                modalFilters.style.display = "block";
+            }
+
+            var closeFiltersButton = document.getElementsByClassName("close-filters")[0];
+            closeFiltersButton.onclick = function () {
+                modalFilters.style.display = "none";
+            }
+
+            window.onclick = function (event) {
+                if (event.target == modalFilters) {
+                    modalFilters.style.display = "none";
+                }
+            }
+        });
+    }
+
+    function validatePrecisionSelection() {
+        const precisions = $('.precisions-column').find('input')
+        precisions.prop('disabled', false);
+    }
+
+    function clearAll() {
+        $('.modal-content-grid-container input:checkbox').each((index, object) => $(object).prop('checked', false));
+        validatePrecisionSelection();
+        validateSelections();
+    }
+
+    function preselectDefaultSettings(graph, modal, appConfig) {
+
+        const defaultSelections = appConfig.DefaultSelections;
+
+        selectDefaultPlatformType(defaultSelections.platformTypes, graph, modal);
+
+        applyPlatformFilters(defaultSelections.platformFilters, modal, graph);
+
+        clearAllSettings(defaultSelections);
+
+        validateSelections();
+        validatePrecisionSelection();
+    }
+
+    function selectDefaultPlatformType(platformTypes, graph, modal) {
+        if (!platformTypes) return;
+
+        const type = platformTypes.data[0];
+        $(`input[data-ietype="${type}"]`).prop('checked', true);
+        renderClientPlatforms(graph, modal);
+    }
+
+    function applyPlatformFilters(platformFilters, modal, graph) {
+        if (!platformFilters) return;
+
+        const filters = modal.find('.selectable-box-container').children('.selectable-box');
+        filters.removeClass('selected');
+
+        platformFilters.data.forEach(selection => {
+            filters.filter(`[data-${platformFilters.name}="${selection}"]`).addClass('selected');
+        });
+
+        renderClientPlatforms(graph, modal);
+    }
+
+    function clearAllSettings(defaultSelections) {
+        clearAll();
+        Object.keys(defaultSelections).forEach(setting => {
+            const { name, data } = defaultSelections[setting];
+            data.forEach(selection => {
+                $(`input[data-${name}="${selection}"]`).prop('checked', true);
+            });
+        });
+    }
+
+    function filterClientPlatforms(graph, ietypes) {
+        return Filter.ByIeTypes(graph, ietypes);
+    }
+
+    function filterPlatforms(graph, ietypes, models) {
+        return Filter.ByTypesAndModels(graph, ietypes, models);
+    }
+
+    function renderClientPlatforms(graph, modal) {
+        var fPlatforms = filterClientPlatforms(graph, getSelectedIeTypes());
+        var platformNames = Graph.getPlatformNames(fPlatforms);
+        $('.platforms-column .checkmark-container').remove();
+
+        const clientPlatforms = platformNames.map((platform) => createCheckMark(platform, 'platform', true));
+
+        var enabledPlatforms = filterPlatforms(graph, getSelectedIeTypes(), getSelectedNetworkModels());
+        enableCheckBoxes(clientPlatforms, enabledPlatforms);
+        modal.find('.platforms-column').append(clientPlatforms);
+
+        enableParmeters(graph, getSelectedClientPlatforms());
+        modal.find('.platforms-column input').on('click', validateSelections);
+    }
+
+    function enableParmeters(graph, clientPlatforms) {
+        var allKpis = Filter.getParameters(graph);
+
+        allKpis.forEach((kpi) => {
+            $(`input[data-kpi="${Graph.capitalizeFirstLetter(kpi)}"]`).prop('disabled', true);
+        })
+
+        var kpis = Filter.ByIeKpis(graph, clientPlatforms);
+        kpis.forEach((kpi) => {
+            $(`input[data-kpi="${Graph.capitalizeFirstLetter(kpi)}"]`).prop('disabled', false);
+        })
+    }
+
+    function createCheckMark(itemLabel, modelLabel, disabled) {
+        const item = $('<label class="checkmark-container">');
+        item.text(itemLabel);
+        const checkbox = $('<input type="checkbox"/>');
+        checkbox.prop('disabled', disabled);
+        const checkboxSpan = $('<span class="checkmark">');
+        item.append(checkbox);
+        item.append(checkboxSpan);
+        checkbox.attr('data-' + modelLabel, itemLabel);
+        return item;
+    }
+
+    // receives a jquery list of items and selects all input checkboxes
+    function selectAllCheckboxes(items) {
+        items.forEach((item) => {
+            item.find(':input').prop('checked', true);
+        });
+    }
+
+    function enableCheckBoxes(items, enabledItems) {
+        items.forEach((item) => {
+            item.find(':input').prop('disabled', true);
+            enabledItems.forEach((platform) => {
+                var tmp = item.find(':input');
+                if (tmp[0].dataset.platform === platform.Platform) {
+                    item.find(':input').prop('checked', true);
+                    item.find(':input').prop('disabled', false);
+                }
+            })
+        })
+    }
+
+    function disableAllCheckboxes(items) {
+        items.forEach((item) => {
+            item.find(':input').prop('disabled', true);
+        })
+    }
+
+    function deSelectAllCheckboxes(items) {
+        items.forEach((item) => {
+            item.find(':input').prop('checked', false);
+        });
+    }
+    function deSelectCheckbox(item) {
+        item.find(':input').prop('checked', false);
+    }
+
+    // =================== HTMLLEGEND =========================
+
+    const getOrCreateLegendList = (chart, id) => {
+        const legendContainer = document.getElementById(id);
+        let listContainer = legendContainer.querySelector('ul');
+
+        if (!listContainer) {
+            listContainer = document.createElement('ul');
+            listContainer.style.display = 'flex';
+            listContainer.style.flexDirection = 'row';
+            listContainer.style.margin = 0;
+            listContainer.style.padding = 0;
+            listContainer.style.paddingLeft = '0px';
+
+            legendContainer.appendChild(listContainer);
+        }
+
+        return listContainer;
+    };
+
+    const htmlLegendPlugin = {
+        id: 'htmlLegend',
+        afterUpdate(chart, args, options) {
+
+            const ul = getOrCreateLegendList(chart, chart.options.plugins.htmlLegend.containerID);
+
+            // Remove old legend items
+            while (ul.firstChild) {
+                ul.firstChild.remove();
+            }
+
+            const items = chart.legend.legendItems;
+            items.forEach(item => {
+                const li = document.createElement('li');
+                li.style.alignItems = 'center';
+                li.style.display = 'block';
+                li.style.flexDirection = 'column';
+                li.style.marginLeft = '4px';
+
+                li.onclick = () => {
+                    chart.toggleDataVisibility(item.index);
+                    chart.update();
+                };
+
+                // Color box
+                const boxSpan = document.createElement('span');
+                boxSpan.style.background = item.fillStyle;
+                boxSpan.style.borderColor = item.strokeStyle;
+                boxSpan.style.borderWidth = item.lineWidth + 'px';
+                boxSpan.style.display = 'inline-block';
+                boxSpan.style.height = '10px';
+                boxSpan.style.marginRight = '4px';
+                boxSpan.style.width = '30px';
+
+                // Text
+                const textContainer = document.createElement('p');
+                textContainer.style.color = '#666';
+                textContainer.style.margin = 0;
+                textContainer.style.padding = 0;
+                textContainer.style.fontSize = '0.6rem';
+                textContainer.style.marginLeft = '3px';
+                textContainer.style.textDecoration = item.hidden ? 'line-through' : '';
+
+                const text = document.createTextNode(item.text);
+                textContainer.appendChild(text);
+
+                li.appendChild(boxSpan);
+                li.appendChild(textContainer);
+                ul.appendChild(li);
+            });
+        }
+    };
+
+    function getChartOptions(containerId, allowedAxisIDs) {
+        const axisConfigs = {
+            x: {
+                title: { display: true, text: 'Request Rate' }
+            },
+            y: {
+                type: 'linear',
+                display: true,
+                position: 'left',
+                title: { display: true, text: 'Throughput [tok/s]' },
+                grid: { drawOnChartArea: true }
+            },
+            y1: {
+                type: 'linear',
+                display: true,
+                position: 'right',
+                title: { display: true, text: 'TPOT Mean Latency' },
+                grid: { drawOnChartArea: true }
+            }
+        };
+
+        return {
+            responsive: true,
+            scales: Object.keys(axisConfigs)
+                .filter(key => allowedAxisIDs.includes(key))
+                .reduce((obj, key) => {
+                    obj[key] = axisConfigs[key];
+                    return obj;
+                }, {}),
+            plugins: {
+                legend: { display: false },
+                htmlLegend: { containerID: containerId }
+            }
+        };
+    }
+
+    function renderData(graph, appConfig, networkModels, ieTypes, platforms, kpis, precisions) {
+        $('.chart-placeholder').empty();
+        $('.modal-footer').empty();
+
+        const display = new ChartDisplay(getChartsDisplayMode(kpis.length), kpis.length);
+        networkModels.forEach((networkModel) => {
+            var chartName = networkModel;
+            var chartSlug = chartName.replace(')', '').replace(' (', '-');
+            var chartContainer = $('<div>');
+            var chevronDown = '<span class="chevron-down-btn"></span>';
+            var chevronRight = '<span style="display:none" class="chevron-right-btn"></span>';
+            $(chevronRight).hide();
+
+            var chartContainerHeader = $(chevronDown + chevronRight + '<span class="graph-chart-title">' + networkModel + '</span>');
+            chartContainerHeader.addClass('graph-chart-title-header');
+            chartContainer.prepend(chartContainerHeader);
+            chartContainer.attr('id', 'ov-chart-container-' + chartSlug);
+
+            chartContainer.addClass('chart-container');
+
+            var filteredNetworkModels = Filter.FilterByNetworkModel(graph, [networkModel]);
+            var filteredIeTypes = Filter.ByIeTypes(filteredNetworkModels, ieTypes);
+            var filteredGraphData = Filter.ByClientPlatforms(filteredIeTypes, platforms);
+            $('.chart-placeholder').append(chartContainer);
+            if (filteredGraphData.length > 0) {
+                createChartWithNewData(filteredGraphData, appConfig, chartContainer, kpis, precisions, display);
+            } else {
+                createEmptyChartContainer(chartContainer);
+            }
+        })
+
+        $(window).off('resize');
+        $(window).resize(() => resetChartsDisplay(display));
+    };
+
+    function createEmptyChartContainer(chartContainer) {
+        chartContainer.append($('<div>').addClass('empty-chart-container').text('No data for this configuration.'));
+    }
+
+    // this function should take the final data set and turn it into graphs
+    // params: GraphData, unused, chartContainer
+    function createChartWithNewData(graphData, appConfig, chartContainer, engines, precisions, display) {
+        var chartWrap = $('<div>');
+        chartWrap.addClass('chart-wrap');
+        chartContainer.append(chartWrap);
+        var graphConfigs = graphData.map((platform) => {
+            var kpiData = [];
+            engines.forEach((engine) => Graph.getDatabyParameter(platform, engine, kpiData));
+            var graphConfig = [];
+            engines.forEach((engine) => {
+                const engineGraphConfig = { engine: engine, config: Graph.getGraphConfig(engine, precisions, JSON.parse(JSON.stringify(appConfig))) };
+                precisions.forEach((precision, index) => {
+                    engineGraphConfig.config.datasets[index].data = kpiData[engine][0].find(el => el[precision])?.[precision];
+                });
+                graphConfig.push(engineGraphConfig);
+                graphConfig.chartTitle = platform.Platform;
+            });
+            return graphConfig
+        })
+
+        // get the client platform labels and create labels for all the graphs
+        var labels = Graph.getPlatformNames(graphData);
+        var labelsContainer = $('<div>');
+        labelsContainer.addClass('chart-labels-container');
+        chartWrap.append(labelsContainer);
+
+        // get the kpi title's and create headers for the graphs
+        var chartGraphsContainer = $('<div>');
+        chartGraphsContainer.addClass('chart-graphs-container');
+        chartWrap.append(chartGraphsContainer);
+
+        graphConfigs.forEach((graphConfig, index) => {
+            const id = getRandomNumber();
+            if (graphConfig.unit === undefined) {
+                graphConfig.unit = 'No unit.';
+            }
+
+            var graphItem = $(`<div id=${id}>`);
+            graphItem.addClass('graph-item');
+            var columnHeaderContainer = $('<div>');
+            columnHeaderContainer.addClass('chart-column-title');
+            var columnIcon = $('<div class="icon">');
+            columnIcon.addClass(graphConfig.iconClass);
+            columnHeaderContainer.append(columnIcon);
+            var columnHeader = $('<div class="chart-header">');
+            columnHeader.append($('<div class="title">' + graphConfig.chartTitle + '</div>'));
+            columnHeaderContainer.append(columnHeader);
+            chartGraphsContainer.append(graphItem);
+            var graphClass = $('<div>');
+            graphClass.addClass('graph-row');
+            graphItem.append(columnHeaderContainer);
+            graphItem.append(graphClass);
+            processMetricNew(labels, graphConfig, graphClass, 'graph-row-column', id);
+            window.setTimeout(() => {
+                var labelsItem = $('<div>');
+                setInitialItemsVisibility(labelsItem, index, display.mode);
+            });
+        });
+        setChartsDisplayDirection(display.mode);
+        adjustHeaderIcons(display.mode);
+    }
+
+    function processMetricNew(labels, datasets, container, widthClass, id) {
+        // ratio for consistent chart label height
+        var heightRatio = (80 + (labels.length * 55));
+        var chart = $('<div>');
+        const containerId = `legend-container-${id}`;
+        const legend = $(`<div id="${containerId}">`);
+        legend.addClass('graph-legend-container');
+        chart.addClass('chart');
+        chart.addClass(widthClass);
+        chart.height(heightRatio);
+        var canvas = $('<canvas>');
+        chart.append(canvas);
+        container.append(chart);
+        container.append(legend);
+        var context = canvas.get(0).getContext('2d');
+        context.canvas.height = heightRatio;
+        window.setTimeout(() => {
+            var labels = [];
+            for (const key in datasets[0].config.datasets[0].data) {
+                labels.push(key);
+            }
+
+            var graphDatas = [];
+            datasets.forEach((engineSet) => {
+                engineSet.config.datasets.forEach((precision) => {
+                    var precData = [];
+                    for (const key in precision.data) {
+                        precData.push(precision.data[key]);
+                    }
+                    graphDatas.push({
+                        label: engineSet.engine + ' ' + precision.label,
+                        data: precData,
+                        borderColor: precision.color,
+                        backgroundColor: precision.color,
+                        yAxisID: precision.label === "Throughput" ? 'y' : 'y1',
+                        fill: false
+                    }
+                    )
+                })
+            })
+
+            let allowedAxisIDs = ['x'];
+            const newAxisIDs = [...new Set(graphDatas.map(item => item.yAxisID))];
+
+            newAxisIDs.forEach(id => {
+                if (!allowedAxisIDs.includes(id)) {
+                    allowedAxisIDs.push(id);
+                }
+            });
+
+            new Chart(context, {
+                type: 'line',
+                data: {
+                    labels: labels,
+                    datasets: graphDatas
+                },
+                options: getChartOptions(containerId, allowedAxisIDs),
+                plugins: [htmlLegendPlugin]
+            });
+        });
+    }
+
+    function getRandomNumber() {
+        return Math.floor(Math.random() * 100000);
+    }
+
+    function resetChartsDisplay(currentDisplay) {
+        const newDisplayMode = getChartsDisplayMode(currentDisplay.numberOfChartsInRow);
+        if (currentDisplay.mode != newDisplayMode) {
+            currentDisplay.mode = newDisplayMode;
+            setChartsDisplayDirection(currentDisplay.mode);
+            adjustLabels(currentDisplay.mode);
+            adjustHeaderIcons(currentDisplay.mode);
+        }
+    }
+
+    function adjustLabels(displayMode) {
+        const firstLabels = $('.chart-labels-container').find('.chart-labels-item:first-child');
+        const labels = $('.chart-labels-container').find('.chart-labels-item');
+        labels.css('padding-top', getLabelsTopPadding(displayMode));
+        if (displayMode == 'column') {
+            labels.show();
+        }
+        else {
+            labels.hide()
+            firstLabels.show();
+        }
+    }
+
+    function adjustHeaderIcons(displayMode) {
+        const icons = $('.graph-item').find('.chart-column-title');
+        if (displayMode == 'rowCompact')
+            icons.css('flex-direction', 'column')
+        else
+            icons.css('flex-direction', 'row')
+    }
+
+    function getLabelsTopPadding(displayMode) {
+        return (displayMode == 'rowCompact') ? 105.91 : 83.912;
+    }
+
+    function setChartsDisplayDirection(displayMode) {
+        const container = $('.chart-placeholder').find('.chart-graphs-container');
+        if (displayMode == 'column') {
+            container.css('flex-direction', 'column');
+        }
+        else {
+            container.css('flex-direction', 'row');
+        }
+    }
+
+    function setInitialItemsVisibility(item, count, displayMode) {
+        if (count == 0 || displayMode == 'column') item.show();
+        else item.hide();
+    }
+
+    function getChartsDisplayMode(numberOfCharts) {
+        switch (numberOfCharts) {
+            case 4:
+                return window.matchMedia('(max-width: 721px)').matches ? 'column'
+                    : window.matchMedia('(max-width: 830px)').matches ? 'rowCompact'
+                        : 'row';
+            case 3:
+                return window.matchMedia('(max-width: 569px)').matches ? 'column'
+                    : window.matchMedia('(max-width: 649px)').matches ? 'rowCompact'
+                        : 'row';
+            case 2:
+                return window.matchMedia('(max-width: 500px)').matches ? 'column'
+                    : 'row';
+            default:
+                return 'row';
+        }
+    }
+});
\ No newline at end of file
diff --git a/docs/sphinx_setup/api/ie_python_api/api.rst b/docs/sphinx_setup/api/ie_python_api/api.rst
index efbe25ee40bcde..6fc754da1246b7 100644
--- a/docs/sphinx_setup/api/ie_python_api/api.rst
+++ b/docs/sphinx_setup/api/ie_python_api/api.rst
@@ -119,6 +119,12 @@ OpenVINO Python API
 
    openvino.runtime.opset15
 
+.. autosummary::
+   :toctree: _autosummary
+   :template: custom-module-template.rst
+
+   openvino.runtime.opset16
+
 .. autosummary::
    :toctree: _autosummary
    :template: custom-module-template.rst
diff --git a/docs/sphinx_setup/conf.py b/docs/sphinx_setup/conf.py
index 01c74de0175bcf..4f2f126935804c 100644
--- a/docs/sphinx_setup/conf.py
+++ b/docs/sphinx_setup/conf.py
@@ -201,6 +201,7 @@
     'js/openvino_sphinx_theme.js',
     'js/splide.min.js',
     'js/sortable_tables.js',
+    'js/graphsLLM.js',
     'js/graphs.js',
     'js/gsearch.js',
     'js/hide_banner.js',
diff --git a/docs/sphinx_setup/index.rst b/docs/sphinx_setup/index.rst
index 47dc76bf16cf29..9d376877b51d08 100644
--- a/docs/sphinx_setup/index.rst
+++ b/docs/sphinx_setup/index.rst
@@ -124,7 +124,7 @@ Places to Begin
 
       Cloud-ready deployments for microservice applications.
 
-      .. button-link:: openvino-workflow/openvino-workflow/model-server/ovms_what_is_openvino_model_server.html
+      .. button-link:: openvino-workflow/model-server/ovms_what_is_openvino_model_server.html
          :color: primary
          :outline:
 
diff --git a/samples/cpp/benchmark_app/main.cpp b/samples/cpp/benchmark_app/main.cpp
index 2cfd15b77afb6e..4dcc1e82924efd 100644
--- a/samples/cpp/benchmark_app/main.cpp
+++ b/samples/cpp/benchmark_app/main.cpp
@@ -60,6 +60,10 @@ bool parse_and_check_command_line(int argc, char* argv[]) {
     if (FLAGS_api != "async" && FLAGS_api != "sync") {
         throw std::logic_error("Incorrect API. Please set -api option to `sync` or `async` value.");
     }
+    if (FLAGS_api == "sync" && FLAGS_nireq > FLAGS_niter) {
+        throw std::logic_error(
+            "Number of iterations should be greater than number of infer requests when using sync API.");
+    }
     if (!FLAGS_hint.empty() && FLAGS_hint != "throughput" && FLAGS_hint != "tput" && FLAGS_hint != "latency" &&
         FLAGS_hint != "cumulative_throughput" && FLAGS_hint != "ctput" && FLAGS_hint != "none") {
         throw std::logic_error("Incorrect performance hint. Please set -hint option to"
diff --git a/src/bindings/python/src/openvino/frontend/pytorch/patch_model.py b/src/bindings/python/src/openvino/frontend/pytorch/patch_model.py
index fb8f70e2a566bc..0d1c4803e3115f 100644
--- a/src/bindings/python/src/openvino/frontend/pytorch/patch_model.py
+++ b/src/bindings/python/src/openvino/frontend/pytorch/patch_model.py
@@ -4,6 +4,7 @@
 # flake8: noqa
 # mypy: ignore-errors
 
+import functools
 import logging
 import torch
 from openvino.frontend.pytorch import ModuleExtension
@@ -70,6 +71,8 @@ def new_forward(*args, **kwargs):
                     Trampoline.stashed_kwargs = kwargs
                 return extension.convert(m, Trampoline.apply, *args, **kwargs)
 
+            # make signature of new_forward same as of forward
+            new_forward = functools.wraps(m.forward)(new_forward)
             setattr(m, orig_forward_name, m.forward)
             m.forward = new_forward
 
diff --git a/src/bindings/python/src/openvino/runtime/opset16/__init__.py b/src/bindings/python/src/openvino/runtime/opset16/__init__.py
new file mode 100644
index 00000000000000..ce52690e919fc3
--- /dev/null
+++ b/src/bindings/python/src/openvino/runtime/opset16/__init__.py
@@ -0,0 +1,9 @@
+# -*- coding: utf-8 -*-
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+# New operations added in Opset16
+from openvino.runtime.opset16.ops import identity
+
+# Operators from previous opsets
+# TODO (ticket: 156877): Add previous opset operators at the end of opset16 development
diff --git a/src/bindings/python/src/openvino/runtime/opset16/ops.py b/src/bindings/python/src/openvino/runtime/opset16/ops.py
new file mode 100644
index 00000000000000..60656f6d993b6a
--- /dev/null
+++ b/src/bindings/python/src/openvino/runtime/opset16/ops.py
@@ -0,0 +1,34 @@
+# -*- coding: utf-8 -*-
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+"""Factory functions for ops added to openvino opset16."""
+from functools import partial
+from typing import Optional
+
+from openvino.runtime import Node
+from openvino.runtime.utils.decorators import nameable_op
+from openvino.runtime.opset_utils import _get_node_factory
+from openvino.runtime.utils.types import NodeInput, as_nodes
+
+_get_node_factory_opset16 = partial(_get_node_factory, "opset16")
+
+# -------------------------------------------- ops ------------------------------------------------
+
+
+@nameable_op
+def identity(
+    data: NodeInput,
+    name: Optional[str] = None,
+) -> Node:
+    """Identity operation is used as a placeholder. It creates a copy of the input to forward to the output.
+
+    :param data: Tensor with data.
+
+    :return: The new node performing Identity operation.
+    """
+    return _get_node_factory_opset16().create(
+        "Identity",
+        as_nodes(data, name=name),
+        {},
+    )
diff --git a/src/bindings/python/tests/test_graph/test_identity.py b/src/bindings/python/tests/test_graph/test_identity.py
new file mode 100644
index 00000000000000..fea1c88858c874
--- /dev/null
+++ b/src/bindings/python/tests/test_graph/test_identity.py
@@ -0,0 +1,31 @@
+# -*- coding: utf-8 -*-
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+
+from openvino.runtime.opset15 import parameter
+from openvino.runtime.opset16 import identity
+from openvino import PartialShape, Type
+
+
+@pytest.mark.parametrize(
+    ("input_shape", "expected_output_shape"),
+    [
+        ([4, 4], PartialShape([4, 4])),
+        ([10, 8, 8], PartialShape([10, 8, 8])),
+        ([-1, -1, -1], PartialShape([-1, -1, -1])),
+        ([10, -1, -1], PartialShape([10, -1, -1])),
+    ],
+)
+@pytest.mark.parametrize("op_name", ["identity", "identityOpset16"])
+def test_inverse_param_inputs(input_shape, expected_output_shape, op_name):
+    data = parameter(input_shape, dtype=np.float32)
+
+    op = identity(data, name=op_name)
+    assert op.get_output_size() == 1
+    assert op.get_type_name() == "Identity"
+    assert op.get_friendly_name() == op_name
+    assert op.get_output_element_type(0) == Type.f32
+    assert op.get_output_partial_shape(0) == expected_output_shape
diff --git a/src/bindings/python/tests/test_transformations/test_pattern_ops.py b/src/bindings/python/tests/test_transformations/test_pattern_ops.py
index 041bf83764e265..24b28061582c68 100644
--- a/src/bindings/python/tests/test_transformations/test_pattern_ops.py
+++ b/src/bindings/python/tests/test_transformations/test_pattern_ops.py
@@ -189,7 +189,7 @@ def test_pattern_optional_root():
 
 
 def test_wrap_type_pattern_type():
-    last_opset_number = 15
+    last_opset_number = 16
     for i in range(1, last_opset_number + 1):
         WrapType(f"opset{i}.Parameter")
         WrapType(f"opset{i}::Parameter")
diff --git a/src/common/snippets/include/snippets/lowered/expressions/buffer_expression.hpp b/src/common/snippets/include/snippets/lowered/expressions/buffer_expression.hpp
index 3dcd98ef0a95fd..9174d9866db503 100644
--- a/src/common/snippets/include/snippets/lowered/expressions/buffer_expression.hpp
+++ b/src/common/snippets/include/snippets/lowered/expressions/buffer_expression.hpp
@@ -38,6 +38,7 @@ class BufferExpression : public Expression {
     size_t get_offset() const { return m_offset; }
     size_t get_allocation_size() const { return m_allocation_size; }
     size_t get_byte_size() const;
+    ov::element::Type get_data_type() const;
 
     void set_reg_group(size_t reg_group) { m_reg_group = reg_group; }
     void set_cluster_id(size_t cluster) { m_cluster_id = cluster; }
diff --git a/src/common/snippets/include/snippets/lowered/loop_info.hpp b/src/common/snippets/include/snippets/lowered/loop_info.hpp
index cc66f5f6ffcc95..23e1f14a8b7f5e 100644
--- a/src/common/snippets/include/snippets/lowered/loop_info.hpp
+++ b/src/common/snippets/include/snippets/lowered/loop_info.hpp
@@ -211,13 +211,20 @@ class UnifiedLoopInfo : public LoopInfo {
         int64_t data_size = 0;
 
         bool is_dynamic() const;
+        bool is_static() const;
+
+        friend bool operator==(const LoopPortDesc& lhs, const LoopPortDesc& rhs);
+        friend bool operator!=(const LoopPortDesc& lhs, const LoopPortDesc& rhs);
     };
     // The structure describes full information about port
     // - TODO [140365] : UnifiedLoopInfo should have the map of LoopPorts and LoopDesc as class field
     //                   instead of the separate vectors with descriptors.
     struct LoopPortInfo {
-        LoopPort port;
-        LoopPortDesc desc;
+        LoopPortInfo() = default;
+        LoopPortInfo(LoopPort port_, LoopPortDesc desc_) : port(std::move(port_)), desc(std::move(desc_)) {}
+
+        LoopPort port = {};
+        LoopPortDesc desc = {};
     };
 
     UnifiedLoopInfo() = default;
@@ -367,6 +374,12 @@ class UnifiedLoopInfo : public LoopInfo {
             caller(m_output_ports[i], m_output_port_descs[i]);
     }
 
+    /**
+     * @brief Return loop port info of an expression port
+     * @param expr_port - expression port.
+     */
+    LoopPortInfo get_loop_port_info(const ExpressionPort& expr_port);
+
 protected:
     /**
      * @brief Clone LoopPortDesc[actual_port_idx] `new_count` times and insert on the place of current desc
diff --git a/src/common/snippets/include/snippets/lowered/pass/define_buffer_clusters.hpp b/src/common/snippets/include/snippets/lowered/pass/define_buffer_clusters.hpp
index 1597eaa2377a50..312abb02abf7b5 100644
--- a/src/common/snippets/include/snippets/lowered/pass/define_buffer_clusters.hpp
+++ b/src/common/snippets/include/snippets/lowered/pass/define_buffer_clusters.hpp
@@ -6,6 +6,8 @@
 
 #include "pass.hpp"
 
+#include "snippets/lowered/loop_info.hpp"
+
 namespace ov {
 namespace snippets {
 namespace lowered {
@@ -45,7 +47,7 @@ class DefineBufferClusters : public RangedPass {
 private:
     using BufferCluster = std::set<BufferExpressionPtr>;
     using BufferClusters = std::vector<BufferCluster>;
-    using BufferPorts = std::unordered_map<BufferExpressionPtr, std::set<size_t>>;
+    using BufferMap = std::unordered_map<BufferExpressionPtr, UnifiedLoopInfo::LoopPortInfo>;
     /**
      * @brief Finds Buffer cluster in set of clusters which contains the target expression with Buffer
      * @param target target expression with Buffer op
@@ -58,76 +60,72 @@ class DefineBufferClusters : public RangedPass {
      * @param target_expr expression with target op - LoopEnd or MemoryAccess op
      * @return boolean value
      */
-    bool is_direct_buffer(const BufferExpressionPtr& buffer_expr, const ExpressionPtr& target_expr) const;
+    static bool is_direct_buffer(const BufferExpressionPtr& buffer_expr, const ExpressionPtr& target_expr);
     /**
      * @brief Creates new buffer cluster if buffer_exprs is missed in clusters. If buffer_exprs is already in clusters, do nothing
      * @param buffer_expr expression with Buffer op
      */
     void create_new_cluster(const BufferExpressionPtr& buffer_expr);
+    /**
+     * @brief Add buffers to the existing clusters
+     * @param existing_cluster existing clusters
+     * @param buffers buffers which will be added to the existing cluster
+     */
+    static void add_buffers_to_cluster(BufferCluster& existing_cluster, const std::set<BufferExpressionPtr>& buffers);
     /**
      * @brief Returns common ID of cluster if all buffer inside have the same Buffer ID. Otherwise returns the default value SIZE_MAX
      *        that means that Buffers in cluster have different IDs.
      * @param cluster set of Buffer expressions - cluster
      * @return common buffer ID or SIZE_MAX - size value
      */
-    size_t get_cluster_buffer_id(const BufferCluster& cluster) const;
+    static size_t get_cluster_buffer_id(const BufferCluster& cluster);
 
     /**
      * @brief Analyzes Loop: if Loop has Buffer ops on inputs and outputs, Loop can read and write from/to the same memory.
+     * @param loop_manager loop manager
      * @param expr_it iterator of Linear IR which refers to the expression with LoopEnd
      */
-    void parse_loop(const LinearIR::constExprIt& expr_it);
+    void parse_loop(const LoopManagerPtr& loop_manager, const LinearIR::constExprIt& expr_it);
     /**
      * @brief Analyzes full MemoryAccess op: if the op has Buffer ops on I/O, the op can read and write from/to the same memory.
      * @param expr expression with full MemoryAccess op
      */
     void parse_memory_access_op(const ExpressionPtr& expr);
     /**
-     * @brief Gets input outputs buffers of Loop
-     * @param loop_expr expression with LoopEnd op
-     * @return unordered map [Expression -> set of input ports] which represents input Buffers of Loop
+     * @brief Find all direct buffers that are connected to the current Loop
+     * @param loop_info current unified loop info
+     * @param loop_expr the target LoopEnd expression
+     * @return input and output buffer maps
      */
-    BufferPorts get_input_buffers(const ExpressionPtr& loop_expr) const;
-    /**
-     * @brief Gets output buffers of Loop
-     * @param loop_expr expression with LoopEnd op
-     * @return unordered map [Expression -> set of input ports] which represents output Buffers of Loop
-     */
-    BufferPorts get_output_buffers(const ExpressionPtr& loop_expr) const;
+    static std::pair<BufferMap, BufferMap> get_direct_buffers(const UnifiedLoopInfoPtr& loop_info, const ExpressionPtr& loop_expr);
     /**
      * @brief Analyzes nested Loops: unite nested buffer clusters if they can reproduce `window` sliding
-     * @param input_buffers unordered map [Expression -> set of input ports] which represents input Buffers of Loop
-     * @param output_buffers unordered map [Expression -> set of output ports (one)] which represents output Buffers of Loop
+     * @param loop_manager loop manager
+     * @param input_buffers unordered map [Expression -> LoopPortInfo] which represents input Buffers of Loop
+     * @param output_buffers unordered map [Expression -> LoopPortInfo] which represents output Buffers of Loop
      * @param outer_loop_end_expr_it iterator of Linear IR which refers to the expression with outer LoopEnd
      */
-    void parse_nested_loops(const BufferPorts& input_buffers, const BufferPorts& output_buffers, const LinearIR::constExprIt& outer_loop_end_expr_it);
+    void parse_nested_loops(const LoopManagerPtr& loop_manager, const BufferMap& input_buffers, const BufferMap& output_buffers,
+                            const LinearIR::constExprIt& outer_loop_end_expr_it);
     /**
-     * @brief Finds the last connected Loop to the target Buffer and returns the corresponding finalization offset
+     * @brief Finds the last connected Loop to the target Buffer and init the corresponding loop port info
+     * @param loop_manager loop manager
      * @param buffer_expr expression with Buffer op
-     * @return finalization offset - int64_t value
-     */
-    int64_t get_buffer_finalization_offset(const BufferExpressionPtr& buffer_expr) const;
-    /**
-     * @brief Check if two Buffer expressions are connected to the same Loop. Set common LoopEnd as `loop` parameter and
-     *        indexes of Loop ports `up_idx` and `down_idx` if Buffers are really neighbours
-     * @param up expression with upper Buffer op
-     * @param down expression with lower Buffer op
-     * @param loop expression with common LoopEnd op
-     * @param up_idx the reference to port index of upper Buffer op to the Loop
-     * @param down_idx the reference to port index of lower Buffer op to the Loop
-     * @return Return True if the Buffers are connected to the same Loop
+     * @param port_info target loop port info to be initialized
+     * @return status - True if loop port has been found. Otherwise, return false - not connected to the Loop.
      */
-    static bool are_buffer_neighbours(const BufferExpressionPtr& up, const BufferExpressionPtr& down, ExpressionPtr& loop,
-                                      size_t& up_idx, size_t& down_idx);
+    static bool init_buffer_last_loop_port_info(const LoopManagerPtr& loop_manager, const BufferExpressionPtr& buffer_expr,
+                                                UnifiedLoopInfo::LoopPortInfo& port_info);
     /**
      * @brief Unite clusters
+     * @param loop_manager loop manager
      * @param inner_cluster_it iterator to inner cluster - buffer cluster is in the loop
      * @param outer_cluster buffer clusters with buffers outside the Loop
      * @param outer_buffer target Buffer from outer_cluster
      * @param is_outer_up true if outer buffer is upper in Linear IR than inner Buffers
      * @return Return True if clusters have been united
      */
-    bool unite_nested_clusters(const BufferClusters::iterator& inner_cluster_it, BufferCluster& outer_cluster,
+    bool unite_nested_clusters(const LoopManagerPtr& loop_manager, const BufferClusters::iterator& inner_cluster_it, BufferCluster& outer_cluster,
                                const BufferExpressionPtr& outer_buffer, bool is_outer_up);
 
     BufferClusters m_clusters;
diff --git a/src/common/snippets/include/snippets/lowered/pass/mark_invariant_shape_path.hpp b/src/common/snippets/include/snippets/lowered/pass/mark_invariant_shape_path.hpp
new file mode 100644
index 00000000000000..6a31a697baca77
--- /dev/null
+++ b/src/common/snippets/include/snippets/lowered/pass/mark_invariant_shape_path.hpp
@@ -0,0 +1,65 @@
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "pass.hpp"
+
+namespace ov {
+namespace snippets {
+namespace lowered {
+namespace pass {
+
+/**
+ * @interface MarkInvariantShapePath
+ * @brief The helper pass for BufferAllocation pipeline:
+ *          - Many buffer-relates passes (SetBufferRegGroup, DefineBufferClusters) depend on loop pointer increments.
+ *            The increments are unknown in dynamic case, so these passes can't set reg groups and clusters efficiently.
+ *            The current pass marks expressions port which will have the same shape. The shape and layout means
+ *            the same loop pointer arithmetic in runtime.
+ * @ingroup snippets
+ */
+class MarkInvariantShapePath: public RangedPass {
+public:
+    OPENVINO_RTTI("MarkInvariantShapePath", "RangedPass")
+    MarkInvariantShapePath() = default;
+
+    /**
+     * @brief Apply the pass to the Linear IR
+     * @param linear_ir the target Linear IR
+     * @return status of the pass
+     */
+    bool run(LinearIR& linear_ir, lowered::LinearIR::constExprIt begin, lowered::LinearIR::constExprIt end) override;
+
+    /**
+     * @brief Returns ID (color) of the current Invariant Shape path for the passed port.
+     *        Ports which have the same IDs of the paths - will have the same shapes in runtime.
+     *        Note: if passed port is input port, the method returns value for source of port connector
+     *              for the passed port. Because the shape is created by output ports of expressions.
+     * @param port target expression port
+     * @return ID
+     */
+    static size_t getInvariantPortShapePath(const ExpressionPort& port);
+
+private:
+    /**
+     * @brief Sets ID (color) of the current Invariant Shape path for the passed output port.
+     *        Ports which have the same IDs of the paths - will have the same shapes in runtime.
+     * @param port target expression port
+     * @param value ID of the path (color)
+     */
+    static void SetInvariantPortShapePath(const ExpressionPort& port, size_t value);
+
+    /**
+     * @brief Return runtime info for the passed expression port
+     * @param port target expression port
+     * @return runtime info map
+     */
+    static ov::RTMap& get_rt_info(const ExpressionPort& port);
+};
+
+} // namespace pass
+} // namespace lowered
+} // namespace snippets
+} // namespace ov
diff --git a/src/common/snippets/include/snippets/lowered/pass/set_buffer_reg_group.hpp b/src/common/snippets/include/snippets/lowered/pass/set_buffer_reg_group.hpp
index cba3f28856be42..dc22ce4beff1a0 100644
--- a/src/common/snippets/include/snippets/lowered/pass/set_buffer_reg_group.hpp
+++ b/src/common/snippets/include/snippets/lowered/pass/set_buffer_reg_group.hpp
@@ -6,6 +6,7 @@
 
 #include "pass.hpp"
 
+#include "snippets/lowered/loop_info.hpp"
 #include "snippets/utils/utils.hpp"
 
 namespace ov {
@@ -38,34 +39,19 @@ class SetBufferRegGroup: public RangedPass {
      * @param linear_ir the target Linear IR
      * @return status of the pass
      */
-    bool run(LinearIR& linear_ir, lowered::LinearIR::constExprIt begin, lowered::LinearIR::constExprIt end) override;
-
-    struct ShiftPtrParams {
-        ShiftPtrParams() = default;
-        ShiftPtrParams(int64_t ds, int64_t pi, int64_t fo) : data_size(ds), ptr_increment(pi), finalization_offset(fo) {}
-        int64_t data_size = 0;
-        int64_t ptr_increment = 0;
-        int64_t finalization_offset = 0;
-
-        inline bool is_static() const {
-            return !utils::is_dynamic_value(ptr_increment) && !utils::is_dynamic_value(finalization_offset);
-        }
-
-        friend bool operator==(const ShiftPtrParams& lhs, const ShiftPtrParams& rhs);
-        friend bool operator!=(const ShiftPtrParams& lhs, const ShiftPtrParams& rhs);
-    };
+    bool run(LinearIR& linear_ir, LinearIR::constExprIt begin, LinearIR::constExprIt end) override;
 
     /**
-     * @brief Check if two Buffers can be in one register group by ShiftPtrParams < data_size, ptr_increment, finalization_offset >
-     * @param lhs Data pointer shift params for first Buffer
-     * @param rhs Data pointer shift params for second Buffer
+     * @brief Check if two Buffers can be in one register group by LoopDesc < data_size, ptr_increment, finalization_offset >
+     * @param lhs LoopPortInfo (Port and Data pointer shift params for first Buffer)
+     * @param rhs LoopPortInfo (Port and Data pointer shift params for second Buffer)
      * @return Returns True if params are valid to reuse one register. Otherwise returns False
      */
-    static bool can_be_in_one_group(const ShiftPtrParams& lhs, const ShiftPtrParams& rhs);
+    static bool can_be_in_one_reg_group(const UnifiedLoopInfo::LoopPortInfo& lhs, const UnifiedLoopInfo::LoopPortInfo& rhs);
 
 private:
     using BufferPool = std::vector<BufferExpressionPtr>;
-    using BufferMap = std::map<BufferExpressionPtr, ShiftPtrParams>;
+    using BufferMap = std::map<BufferExpressionPtr, UnifiedLoopInfo::LoopPortInfo>;
 
     /**
      * @brief Get Buffer Index in Buffer set
@@ -76,11 +62,14 @@ class SetBufferRegGroup: public RangedPass {
     static size_t get_buffer_idx(const BufferExpressionPtr& target, const BufferPool& pool);
     /**
      * @brief Create adjacency matrix for Buffer system. See comment in the method for more details.
-     * @param linear_ir the target Linear IR
+     * @param loop_manager the loop manager
+     * @param begin begin iterator
+     * @param end end iterator
      * @param pool set of Buffers from the Linear IR
      * @return adjacency matrix where True value means that Buffers are adjacent and cannot have the same ID
      */
-    static std::vector<bool> create_adjacency_matrix(lowered::LinearIR::constExprIt begin, lowered::LinearIR::constExprIt end, const BufferPool& pool);
+    static std::vector<bool> create_adjacency_matrix(const LoopManagerPtr& loop_manager, LinearIR::constExprIt begin, LinearIR::constExprIt end,
+                                                     const BufferPool& pool);
     /**
      * @brief Algorithm of Graph coloring where vertices are Buffers
      * @param buffers set of Buffers from the Linear IR
@@ -99,25 +88,23 @@ class SetBufferRegGroup: public RangedPass {
      * @param buffers set of Buffers from the Linear IR
      * @param adj Target adjacency matrix
      */
-    static void update_adj_matrix(const std::pair<BufferExpressionPtr, ShiftPtrParams>& lhs,
-                                  const std::pair<BufferExpressionPtr, ShiftPtrParams>& rhs,
-                                  const BufferPool& buffers,
+    static void update_adj_matrix(const BufferMap::value_type& lhs, const BufferMap::value_type& rhs, const BufferPool& buffers,
                                   std::vector<bool>& adj);
+
     /**
      * @brief Check if two Buffers are adjacent and cannot have the same ID
-     * @param lhs Pair where first value is Expression with first Buffer and second value is data pointer shift params for it
-     * @param rhs Pair where first value is Expression with second Buffer and second value is data pointer shift params for it
+     * @param lhs LoopPortInfo (Port and Data pointer shift params for first Buffer)
+     * @param rhs LoopPortInfo (Port and Data pointer shift params for second Buffer)
      * @return Returns True if they are adjacent, otherwise returns False
      */
-    static bool are_adjacent(const std::pair<BufferExpressionPtr, ShiftPtrParams>& lhs,
-                             const std::pair<BufferExpressionPtr, ShiftPtrParams>& rhs);
+    static bool are_adjacent(const BufferMap::value_type& lhs, const BufferMap::value_type& rhs);
 
     /**
-     * @brief Find all buffers that are connected to the current LoopEnd
-     * @param loop_end_expr expression of the target LoopEnd
-     * @return buffer map [buffer expr -> ShiftDataPtrs]
+     * @brief Find all buffers that are connected to the current Loop
+     * @param loop_info current unified loop info
+     * @return buffer map
      */
-    static BufferMap get_buffer_loop_neighbours(const ExpressionPtr& loop_end_expr);
+    static BufferMap get_buffer_loop_neighbours(const UnifiedLoopInfoPtr& loop_info);
     /**
      * @brief Find all buffers that are inside the current Loop.
      * @param loop_end_it expression iterator in LinearIR of the target LoopEnd
diff --git a/src/common/snippets/include/snippets/utils/utils.hpp b/src/common/snippets/include/snippets/utils/utils.hpp
index f7e584d48a905c..ff4646f24d03b7 100644
--- a/src/common/snippets/include/snippets/utils/utils.hpp
+++ b/src/common/snippets/include/snippets/utils/utils.hpp
@@ -91,6 +91,12 @@ static inline auto rnd_up(const T lhs, const U rhs) -> decltype(div_up(lhs, rhs)
     return div_up_res * rhs;
 }
 
+static inline bool is_planar_layout(const std::vector<size_t>& order) {
+    for (size_t i = 0; i < order.size(); ++i)
+        if (order[i] != i) return false;
+    return true;
+}
+
 inline bool is_dynamic_vdims(const VectorDims& shape) {
     return std::any_of(shape.cbegin(), shape.cend(), [](size_t v){ return is_dynamic_value(v); });
 }
diff --git a/src/common/snippets/src/lowered/expression.cpp b/src/common/snippets/src/lowered/expression.cpp
index aaa71612cef706..1952b93017aab5 100644
--- a/src/common/snippets/src/lowered/expression.cpp
+++ b/src/common/snippets/src/lowered/expression.cpp
@@ -170,11 +170,6 @@ ExpressionPtr Expression::clone() const {
 }
 
 bool Expression::visit_attributes(AttributeVisitor &visitor) {
-    auto is_planar_layout = [](const std::vector<size_t>& layout) {
-        for (size_t i = 0; i < layout.size(); ++i)
-            if (layout[i] != i) return false;
-        return true;
-    };
     auto subtensor2str = [](const VectorDims& subtensor) {
         std::stringstream ss;
         for (size_t i = 0; i < subtensor.size(); ++i) {
@@ -203,7 +198,7 @@ bool Expression::visit_attributes(AttributeVisitor &visitor) {
             subtensors.emplace_back("in_subtensor_" + std::to_string(i), subtensor2str(subtensor));
 
         const auto& layout = desc->get_layout();
-        if (!layout.empty() && !is_planar_layout(layout))
+        if (!layout.empty() && !utils::is_planar_layout(layout))
             layouts.emplace_back("in_layout_" + std::to_string(i), layout);
 
         in_reg_types.emplace_back(regTypeToStr(desc->get_reg().type));
@@ -220,7 +215,7 @@ bool Expression::visit_attributes(AttributeVisitor &visitor) {
             subtensors.emplace_back("out_subtensor_" + std::to_string(i), subtensor2str(subtensor));
 
         const auto& layout = desc->get_layout();
-        if (!layout.empty() && !is_planar_layout(layout))
+        if (!layout.empty() && !utils::is_planar_layout(layout))
             layouts.emplace_back("out_layout_" + std::to_string(i), layout);
 
         out_reg_types.emplace_back(regTypeToStr(desc->get_reg().type));
diff --git a/src/common/snippets/src/lowered/expressions/buffer_expression.cpp b/src/common/snippets/src/lowered/expressions/buffer_expression.cpp
index acc742ff196407..a8b3bb2034b105 100644
--- a/src/common/snippets/src/lowered/expressions/buffer_expression.cpp
+++ b/src/common/snippets/src/lowered/expressions/buffer_expression.cpp
@@ -25,12 +25,15 @@ ExpressionPtr BufferExpression::clone() const {
 }
 
 bool BufferExpression::visit_attributes(AttributeVisitor &visitor) {
+    Expression::visit_attributes(visitor);
     auto allocation_size = utils::value2str(m_allocation_size);
     auto offset = utils::value2str(m_offset);
+    auto prc = get_data_type();
     visitor.on_attribute("allocation_size", allocation_size);
     visitor.on_attribute("offset", offset);
     visitor.on_attribute("reg_group", m_reg_group);
     visitor.on_attribute("cluster_id", m_cluster_id);
+    visitor.on_attribute("data_type", prc);
     return true;
 }
 
@@ -38,9 +41,13 @@ bool BufferExpression::is_defined() const {
     return !utils::is_dynamic_value(m_allocation_size);
 }
 
+ov::element::Type BufferExpression::get_data_type() const {
+    return get_node()->get_output_element_type(0);
+}
+
 size_t BufferExpression::get_byte_size() const {
     if (is_defined())
-        return m_allocation_size * get_node()->get_output_element_type(0).size();
+        return m_allocation_size * get_data_type().size();
     return utils::get_dynamic_value<size_t>();
 }
 
diff --git a/src/common/snippets/src/lowered/loop_info.cpp b/src/common/snippets/src/lowered/loop_info.cpp
index 954cc180a1527b..1c856869878b80 100644
--- a/src/common/snippets/src/lowered/loop_info.cpp
+++ b/src/common/snippets/src/lowered/loop_info.cpp
@@ -99,7 +99,7 @@ template<>
 std::vector<LoopPort>::iterator LoopInfo::find_loop_port(const ExpressionPort& expr_port) {
     auto& ports = expr_port.get_type() == ExpressionPort::Input ? m_input_ports : m_output_ports;
     const auto it = std::find_if(ports.begin(), ports.end(),
-                                [&expr_port](const LoopPort& port) { return *port.expr_port.get() == expr_port; });
+                                [&expr_port](const LoopPort& port) { return *port.expr_port == expr_port; });
     return it;
 }
 
@@ -176,6 +176,19 @@ bool UnifiedLoopInfo::LoopPortDesc::is_dynamic() const {
     return utils::is_dynamic_value(ptr_increment) || utils::is_dynamic_value(finalization_offset);
 }
 
+bool UnifiedLoopInfo::LoopPortDesc::is_static() const {
+    return !is_dynamic();
+}
+
+bool operator==(const UnifiedLoopInfo::LoopPortDesc& lhs, const UnifiedLoopInfo::LoopPortDesc& rhs) {
+    if (&lhs == &rhs)
+        return true;
+    return lhs.ptr_increment == rhs.ptr_increment && lhs.finalization_offset == rhs.finalization_offset && lhs.data_size == rhs.data_size;
+}
+bool operator!=(const UnifiedLoopInfo::LoopPortDesc& lhs, const UnifiedLoopInfo::LoopPortDesc& rhs) {
+    return !(rhs == lhs);
+}
+
 UnifiedLoopInfo::UnifiedLoopInfo(size_t work_amount, size_t increment,
                                  const std::vector<LoopPort>& entries, const std::vector<LoopPort>& exits,
                                  const SpecificIterationHandlers& handlers)
@@ -321,6 +334,18 @@ void UnifiedLoopInfo::sort_ports() {
     reorder(m_output_ports, m_output_port_descs);
 }
 
+UnifiedLoopInfo::LoopPortInfo UnifiedLoopInfo::get_loop_port_info(const ExpressionPort& expr_port) {
+    OPENVINO_ASSERT(is_loop_port(expr_port), "Failed get_loop_port: expr_port is not a loop port");
+    const auto is_input = expr_port.get_type() == ExpressionPort::Input;
+    const auto& ports = is_input ? m_input_ports : m_output_ports;
+    const auto& descs = is_input ? m_input_port_descs : m_output_port_descs;
+    const auto it = std::find_if(ports.begin(), ports.end(),
+                                [&expr_port](const LoopPort& port) { return *port.expr_port == expr_port; });
+    const auto index = static_cast<size_t>(std::distance(ports.cbegin(), it));
+    OPENVINO_ASSERT(index < ports.size() && index < descs.size(), "LoopPortInfo has not been found!");
+    return {ports[index], descs[index]};
+}
+
 void UnifiedLoopInfo::replace_with_cloned_descs(size_t actual_port_idx, size_t new_count, bool is_input) {
     auto& descs = is_input ? m_input_port_descs : m_output_port_descs;
     std::vector<LoopPortDesc> target_shifts(new_count, descs[actual_port_idx]);
diff --git a/src/common/snippets/src/lowered/loop_port.cpp b/src/common/snippets/src/lowered/loop_port.cpp
index 990b2801beccb8..52f59bb1fa4d35 100644
--- a/src/common/snippets/src/lowered/loop_port.cpp
+++ b/src/common/snippets/src/lowered/loop_port.cpp
@@ -30,7 +30,7 @@ std::shared_ptr<LoopPort> LoopPort::clone_with_new_expr(const ExpressionPtr& new
 bool operator==(const LoopPort& lhs, const LoopPort& rhs) {
     if (&lhs == &rhs)
         return true;
-    return lhs.expr_port == rhs.expr_port && lhs.is_incremented == rhs.is_incremented && lhs.dim_idx == rhs.dim_idx;
+    return *lhs.expr_port == *rhs.expr_port && lhs.is_incremented == rhs.is_incremented && lhs.dim_idx == rhs.dim_idx;
 }
 
 bool operator!=(const LoopPort& lhs, const LoopPort& rhs) {
@@ -38,8 +38,8 @@ bool operator!=(const LoopPort& lhs, const LoopPort& rhs) {
 }
 
 bool operator<(const LoopPort& lhs, const LoopPort& rhs) {
-    return (lhs.expr_port < rhs.expr_port) ||
-           (lhs.expr_port == rhs.expr_port &&
+    return (*lhs.expr_port < *rhs.expr_port) ||
+           (*lhs.expr_port == *rhs.expr_port &&
             (lhs.is_incremented < rhs.is_incremented ||
              (lhs.is_incremented == rhs.is_incremented && lhs.dim_idx < rhs.dim_idx)));
 }
diff --git a/src/common/snippets/src/lowered/pass/allocate_buffers.cpp b/src/common/snippets/src/lowered/pass/allocate_buffers.cpp
index f76c4097b38f38..0269c65109b701 100644
--- a/src/common/snippets/src/lowered/pass/allocate_buffers.cpp
+++ b/src/common/snippets/src/lowered/pass/allocate_buffers.cpp
@@ -12,7 +12,7 @@
 #include "snippets/lowered/pass/define_buffer_clusters.hpp"
 #include "snippets/lowered/pass/normalize_buffer_reg_groups.hpp"
 #include "snippets/lowered/pass/propagate_buffer_offset.hpp"
-#include "snippets/pass/tokenization.hpp"
+#include "snippets/lowered/pass/mark_invariant_shape_path.hpp"
 #include "snippets/itt.hpp"
 #include "snippets/utils/utils.hpp"
 
@@ -30,6 +30,7 @@ bool AllocateBuffers::run(lowered::LinearIR& linear_ir, lowered::LinearIR::const
     PassPipeline pipeline;
     pipeline.register_pass<ComputeBufferAllocationSize>();
     if (m_is_optimized_mode) {
+        pipeline.register_pass<MarkInvariantShapePath>();
         pipeline.register_pass<SetBufferRegGroup>();
         pipeline.register_pass<DefineBufferClusters>();
         pipeline.register_pass<SolveBufferMemory>(buffer_scratchpad_size);
diff --git a/src/common/snippets/src/lowered/pass/define_buffer_clusters.cpp b/src/common/snippets/src/lowered/pass/define_buffer_clusters.cpp
index c43b5d63a358c6..e8132d62be0cc9 100644
--- a/src/common/snippets/src/lowered/pass/define_buffer_clusters.cpp
+++ b/src/common/snippets/src/lowered/pass/define_buffer_clusters.cpp
@@ -4,24 +4,42 @@
 
 #include "snippets/lowered/pass/define_buffer_clusters.hpp"
 
+#include "snippets/lowered/pass/mark_invariant_shape_path.hpp"
 #include "snippets/lowered/pass/set_buffer_reg_group.hpp"
+#include "snippets/lowered/loop_manager.hpp"
 #include "snippets/snippets_isa.hpp"
 #include "snippets/utils/utils.hpp"
 #include "snippets/itt.hpp"
 
+
 namespace ov {
 namespace snippets {
 namespace lowered {
 namespace pass {
 
-using ShiftPtrParams = SetBufferRegGroup::ShiftPtrParams;
+namespace {
+
+// Find Loops which are connected to the current `buffer_expr` (consumer of Buffer is port of these Loops)
+std::vector<size_t> get_connected_loops(const BufferExpressionPtr& buffer_expr, const ExpressionPtr& consumer_expr) {
+    // [133463] Remove it please
+    if (ov::is_type<op::LoopEnd>(consumer_expr->get_node()))
+        return {};
+    const auto& buffer_loops_ids = buffer_expr->get_loop_ids();
+    const auto& consumer_loop_ids = consumer_expr->get_loop_ids();
+    OPENVINO_ASSERT(buffer_loops_ids.size() <= consumer_loop_ids.size(), "Buffer with consumer are in incorrect loops");
+    const auto mismatched_its = std::mismatch(buffer_loops_ids.begin(), buffer_loops_ids.end(), consumer_loop_ids.begin());
+    return {mismatched_its.second, consumer_loop_ids.cend()};
+}
+} // namespace
+
+using LoopPortInfo = UnifiedLoopInfo::LoopPortInfo;
 
 DefineBufferClusters::BufferClusters::iterator DefineBufferClusters::find_cluster_by_expr(const BufferExpressionPtr& target) {
     return std::find_if(m_clusters.begin(), m_clusters.end(),
                         [&target](const BufferCluster& cluster) { return cluster.count(target) > 0; });
 }
 
-bool DefineBufferClusters::is_direct_buffer(const BufferExpressionPtr& buffer_expr, const ExpressionPtr& target_expr) const {
+bool DefineBufferClusters::is_direct_buffer(const BufferExpressionPtr& buffer_expr, const ExpressionPtr& target_expr) {
     return buffer_expr && buffer_expr->get_loop_ids() == target_expr->get_loop_ids();
 }
 
@@ -33,7 +51,16 @@ void DefineBufferClusters::create_new_cluster(const BufferExpressionPtr& buffer_
     }
 }
 
-size_t DefineBufferClusters::get_cluster_buffer_id(const BufferCluster& cluster) const {
+void DefineBufferClusters::add_buffers_to_cluster(BufferCluster& existing_cluster, const std::set<BufferExpressionPtr>& buffers) {
+    existing_cluster.insert(buffers.cbegin(), buffers.cend());
+    // All buffers in one cluster must be only static or dynamic (no mixes).
+    if (std::any_of(existing_cluster.cbegin(), existing_cluster.cend(), [](const BufferExpressionPtr& buffer) { return !buffer->is_defined(); })) {
+        for (const auto& buffer : existing_cluster)
+            buffer->set_allocation_size(utils::get_dynamic_value<size_t>());
+    }
+}
+
+size_t DefineBufferClusters::get_cluster_buffer_id(const BufferCluster& cluster) {
     OPENVINO_ASSERT(!cluster.empty(), "Buffer cluster is empty!");
     const auto id = cluster.cbegin()->get()->get_reg_group();
     if (std::all_of(cluster.cbegin(), cluster.cend(), [&id](const BufferExpressionPtr& expr) { return expr->get_reg_group() == id; })) {
@@ -42,141 +69,121 @@ size_t DefineBufferClusters::get_cluster_buffer_id(const BufferCluster& cluster)
     return SIZE_MAX;
 }
 
-DefineBufferClusters::BufferPorts DefineBufferClusters::get_input_buffers(const ExpressionPtr& loop_expr) const {
-    BufferPorts input_buffers;
-
-    const auto loop_end = ov::as_type_ptr<op::LoopEnd>(loop_expr->get_node());
-    const auto in_count = loop_end->get_input_num();
-    const auto& connectors = loop_expr->get_input_port_connectors();
-
-    // Input Buffers
-    for (size_t i = 0; i < in_count; ++i) {
-        const auto& source_expr = ov::as_type_ptr<BufferExpression>(connectors[i]->get_source().get_expr());
-        if (!is_direct_buffer(source_expr, loop_expr))
+std::pair<DefineBufferClusters::BufferMap, DefineBufferClusters::BufferMap> DefineBufferClusters::get_direct_buffers(const UnifiedLoopInfoPtr& loop_info,
+                                                                                                                     const ExpressionPtr& loop_expr) {
+    BufferMap input_buffers;
+    const auto& loop_inputs = loop_info->get_input_ports_info();
+    for (const auto& port_info : loop_inputs) {
+        const auto& buffer_expr = ov::as_type_ptr<BufferExpression>(port_info.port.expr_port->get_port_connector_ptr()->get_source().get_expr());
+        if (!is_direct_buffer(buffer_expr, loop_expr))
+            continue;
+        if (input_buffers.count(buffer_expr) > 0) {
+            const auto& port_desc = port_info.desc;
+            OPENVINO_ASSERT(input_buffers[buffer_expr].desc == port_desc,
+                            "Invalid data pointer shifts: If Buffer has several consumers, this consumers must have the same shifts or zero");
             continue;
-        // Save as input Buffer
-        const auto ret = input_buffers.insert(std::make_pair(source_expr, std::set<size_t>{ i })).second;
-        if (!ret)
-            input_buffers[source_expr].insert(i);
+        }
+        input_buffers[buffer_expr] = port_info;
     }
-    return input_buffers;
-}
-
-DefineBufferClusters::BufferPorts DefineBufferClusters::get_output_buffers(const ExpressionPtr& loop_expr) const {
-    BufferPorts output_buffers;
 
-    const auto loop_end = ov::as_type_ptr<op::LoopEnd>(loop_expr->get_node());
-    const auto in_count = loop_end->get_input_num();
-    const auto out_count = loop_end->get_output_num();
-    const auto& connectors = loop_expr->get_input_port_connectors();
-
-    for (size_t i = in_count; i < in_count + out_count; ++i) {
-        for (const auto& consumer : connectors[i]->get_consumers()) {
-            const auto& consumer_expr =  ov::as_type_ptr<BufferExpression>(consumer.get_expr());
-            if (!is_direct_buffer(consumer_expr, loop_expr))
+    BufferMap output_buffers;
+    const auto& loop_outputs = loop_info->get_output_ports_info();
+    for (const auto& port_info : loop_outputs) {
+        const auto& consumer_inputs = port_info.port.expr_port->get_port_connector_ptr()->get_consumers();
+        for (const auto& consumer_input : consumer_inputs) {
+            const auto& buffer_expr = ov::as_type_ptr<BufferExpression>(consumer_input.get_expr());
+            if (!is_direct_buffer(buffer_expr, loop_expr))
                 continue;
-            // Save as output Buffer
-            output_buffers[consumer_expr] = { i };
+            OPENVINO_ASSERT(output_buffers.count(buffer_expr) == 0, "Only one Buffer can be on node output!");
+            output_buffers[buffer_expr] = port_info;
         }
     }
-    return output_buffers;
+
+    return std::make_pair(input_buffers, output_buffers);
 }
 
-void DefineBufferClusters::parse_loop(const LinearIR::constExprIt& expr_it) {
+void DefineBufferClusters::parse_loop(const LoopManagerPtr& loop_manager, const LinearIR::constExprIt& expr_it) {
     const auto& expr = *expr_it;
-    const auto loop_end = ov::as_type_ptr<op::LoopEnd>(expr->get_node());
-    const auto& ptr_increments = loop_end->get_ptr_increments();
-    const auto& final_offsets = loop_end->get_finalization_offsets();
-    const auto& data_sizes = loop_end->get_element_type_sizes();
+    const auto& loop_end = ov::as_type_ptr<op::LoopEnd>(expr->get_node());
+    const auto& loop_info = loop_manager->get_loop_info<UnifiedLoopInfo>(loop_end->get_id());
 
-    // [ Expression -> Port indexes ]
-    const auto input_buffers = get_input_buffers(expr);
-    const auto output_buffers = get_output_buffers(expr);
+    BufferMap input_buffers, output_buffers;
+    std::tie(input_buffers, output_buffers) = get_direct_buffers(loop_info, expr);
 
     for (const auto& in : input_buffers)
         create_new_cluster(in.first);
 
     std::set<ExpressionPtr> visited_buffers;
     for (const auto& out : output_buffers) {
-        const auto output_buffer_expr = out.first;
-        const auto output_buffer_port_idx = *(out.second.cbegin());  // Output port is always one
+        const auto& output_buffer_expr = out.first;
+        const auto& output_buffer_port_info = out.second;
         bool has_been_added = false;
 
         for (const auto& in : input_buffers) {
             const auto& input_buffer_expr = in.first;
+            const auto& input_buffer_port_info = in.second;
             if (visited_buffers.count(input_buffer_expr) > 0)
                 continue;
 
-            // If allocated sizes of buffers are unkown on compilation stage (dynamic),
-            // we cannot be sure that they're will be the same in runtime.
-            if (!input_buffer_expr->is_defined()|| !output_buffer_expr->is_defined())
+            // Memory can be reused if reading and writing are executed proportionally:
+            //  - output buffer can have precision with data size less than input buffer
+            if ((input_buffer_expr->get_data_type().size() < output_buffer_expr->get_data_type().size()))
                 continue;
 
-            // Memory can be reused if reading and writing are executed proportionally:
-            //  - the same reading/writing order
-            //  - the same buffer memory sizes
-            if ((input_buffer_expr->get_byte_size() != output_buffer_expr->get_byte_size()) ||
-                (input_buffer_expr->get_output_port_descriptor(0)->get_layout() != output_buffer_expr->get_input_port_descriptor(0)->get_layout()))
+            const auto in_path = MarkInvariantShapePath::getInvariantPortShapePath(*input_buffer_port_info.port.expr_port);
+            const auto out_path = MarkInvariantShapePath::getInvariantPortShapePath(*output_buffer_port_info.port.expr_port);
+            //  - Memory can be reused if there are the same loop pointer increments (data size, final offsets, ptr increments).
+            //    For that, loop ports with buffers should be on the same shape-path and have the same value of `is_incremented`.
+            if (in_path != out_path || input_buffer_port_info.port.is_incremented != output_buffer_port_info.port.is_incremented)
                 continue;
 
-            // Also memory can be reused if there are the same ShiftPtrParams (data size, final offsets, ptr increments)
-            const auto& input_buffer_ports = in.second;
-            for (const auto& input_buffer_port_idx : input_buffer_ports) {
-                const auto input_params =
-                    ShiftPtrParams(data_sizes[input_buffer_port_idx], ptr_increments[input_buffer_port_idx], final_offsets[input_buffer_port_idx]);
-                const auto output_params =
-                    ShiftPtrParams(data_sizes[output_buffer_port_idx], ptr_increments[output_buffer_port_idx], final_offsets[output_buffer_port_idx]);
-
-                // If data pointer shift parameters are unknown on model compilation stage (dynamic),
-                // we cannot be sure that these data pointers will be proportionally shifted in runtime.
-                if (input_params.is_static() && output_params.is_static() && input_params == output_params) {
-                    const auto cluster_it = find_cluster_by_expr(input_buffer_expr);
-                    OPENVINO_ASSERT(cluster_it != m_clusters.end(), "Buffer on inputs of Loop must be already saved in clusters");
-                    // Add to the existing cluster
-                    has_been_added = cluster_it->insert(output_buffer_expr).second;
-                    OPENVINO_ASSERT(has_been_added, "Buffer has not been saved in cluster");
-                    // Remove input buffer because we have already use its memory
-                    visited_buffers.insert(input_buffer_expr);
-                    break;
-                }
+            //  - Memory can be shared if Buffer has the same allocation size.
+            if (input_buffer_expr->is_defined() && output_buffer_expr->is_defined()) {
+                if (input_buffer_expr->get_allocation_size() != output_buffer_expr->get_allocation_size())
+                    continue;
+            } else {
+                // If allocation sizes are undefined, we can check if they have the same allocation sizes in runtime:
+                //  - they should calculate allocation size using the common algorithm from `BufferExpression::init_allocation_size`.
+                if (!utils::everyone_is(BufferExpression::get_type_info_static(), input_buffer_expr->get_type_info(), output_buffer_expr->get_type_info()))
+                    continue;
             }
-            if (has_been_added) break;
+
+            const auto cluster_it = find_cluster_by_expr(input_buffer_expr);
+            OPENVINO_ASSERT(cluster_it != m_clusters.end(), "Buffer on inputs of Loop must be already saved in clusters");
+            // Add to the existing cluster
+            add_buffers_to_cluster(*cluster_it, {output_buffer_expr});
+            // Remove input buffer because we have already use its memory
+            visited_buffers.insert(input_buffer_expr);
+            has_been_added = true;
+            break;
         }
         if (!has_been_added) {
-            m_clusters.push_back(BufferCluster{output_buffer_expr});
+            create_new_cluster(output_buffer_expr);
         }
     }
 
     // Check Buffers inside to possible memory reusing using `window` sliding
-    parse_nested_loops(input_buffers, output_buffers, expr_it);
+    parse_nested_loops(loop_manager, input_buffers, output_buffers, expr_it);
 }
 
-void DefineBufferClusters::parse_nested_loops(const BufferPorts& input_buffers, const BufferPorts& output_buffers,
-                                              const LinearIR::constExprIt& outer_loop_end_expr_it) {
+void DefineBufferClusters::parse_nested_loops(const LoopManagerPtr& loop_manager, const BufferMap& input_buffers,
+                                              const BufferMap& output_buffers, const LinearIR::constExprIt& outer_loop_end_expr_it) {
     if (input_buffers.empty() && output_buffers.empty())
         return;
 
-    // The inner Buffer can reuse memory of the outer Buffer using `window` sliding only if:
-    //  - The finalization offset of the latest Loop connected to the inner Buffer is equal to pointer increment of outer Buffer to emulate `window` sliding
-    //  - This outer Buffer should have the same Buffer ID as inner to move data ptr of inner Buffer after each outer Loop iteration.
-    //    It's needed because all Loops reset data pointers of connected Buffer after full work.
-    //    To avoid rewriting of outer Buffer data we have to have the same Buffer ID (GPR) to proportionally shift pointers both Buffers.
-
-    auto can_be_data_ptr_proportionally_shifted = [](int64_t outer_buffer_ptr_increment, int64_t outer_buffer_data_size,
-                                                     int64_t inner_buffer_final_offsets, int64_t inner_buffer_data_size) {
-        // If data pointer shift parameters are unknown on model compilation stage (dynamic),
-        // we cannot be sure that these data pointers will be proportionally shifted in runtime.
-        if (utils::is_dynamic_value(outer_buffer_ptr_increment) || utils::is_dynamic_value(inner_buffer_final_offsets))
+    auto can_be_data_ptr_proportionally_shifted = [](const LoopPortInfo& outer_port_info, const LoopPortInfo& inner_port_info) {
+        // Outer Buffer ptr should be shifted to emulate "window" sliding
+        const auto& outer_desc = outer_port_info.desc;
+        if (!outer_port_info.port.is_incremented || (!utils::is_dynamic_value(outer_desc.ptr_increment) && outer_desc.ptr_increment == 0))
             return false;
-        return (outer_buffer_ptr_increment != 0) &&
-               ((inner_buffer_data_size * inner_buffer_final_offsets * -1) == outer_buffer_ptr_increment * outer_buffer_data_size);
-    };
 
-    const auto outer_loop_end = ov::as_type_ptr<op::LoopEnd>(outer_loop_end_expr_it->get()->get_node());
-    const auto outer_loop_begin = outer_loop_end->get_loop_begin();
-    const auto& outer_ptr_increments = outer_loop_end->get_ptr_increments();
-    const auto& outer_data_sizes = outer_loop_end->get_element_type_sizes();
+        OPENVINO_ASSERT(inner_port_info.port.expr_port && outer_port_info.port.expr_port, "Expression ports are nullptr!");
+        // we can be sure that these data pointers will be proportionally shifted if they're on the same invariant shape path
+        return MarkInvariantShapePath::getInvariantPortShapePath(*inner_port_info.port.expr_port) ==
+               MarkInvariantShapePath::getInvariantPortShapePath(*outer_port_info.port.expr_port);
+    };
 
+    const auto outer_loop_begin = ov::as_type_ptr<op::LoopEnd>(outer_loop_end_expr_it->get()->get_node())->get_loop_begin();
     for (auto it = std::reverse_iterator<LinearIR::constExprIt>(outer_loop_end_expr_it); (*it)->get_node() != outer_loop_begin; ++it) {
         const auto& inner_expr = *it;
         if (const auto inner_buffer_expr = ov::as_type_ptr<BufferExpression>(inner_expr)) {
@@ -185,9 +192,12 @@ void DefineBufferClusters::parse_nested_loops(const BufferPorts& input_buffers,
             const auto inner_cluster_id = get_cluster_buffer_id(*inner_cluster_it);
             if (inner_cluster_id == SIZE_MAX) continue;
 
-            const auto final_offset = get_buffer_finalization_offset(inner_buffer_expr);
+            // If inner Buffer is not connected to the Loop - `window` sliding effect is not possible
+            LoopPortInfo final_loop_info;
+            if (!init_buffer_last_loop_port_info(loop_manager, inner_buffer_expr, final_loop_info))
+                continue;
 
-            auto unite = [&](const BufferPorts& ports, const bool is_input) {
+            auto unite = [&](const BufferMap& ports, const bool is_input) {
                 bool applied = false;
                 for (const auto& port : ports) {
                     const auto cluster_it = find_cluster_by_expr(port.first);
@@ -196,17 +206,15 @@ void DefineBufferClusters::parse_nested_loops(const BufferPorts& input_buffers,
                     if (cluster_it == inner_cluster_it) continue;
                     // Buffer from one cluster must be only defined (with known allocation_size) or dynamic (with unknown allocation_size)
                     if (inner_buffer_expr->is_defined() != port.first->is_defined()) continue;
-
-                    bool can_be_reused = true;
-                    for (const auto idx : port.second) {
-                        can_be_reused = can_be_reused &&
-                            can_be_data_ptr_proportionally_shifted(outer_ptr_increments[idx], outer_data_sizes[idx],
-                                                                   final_offset, inner_buffer_expr->get_node()->get_element_type().size());
-                    }
-                    if (!can_be_reused)
-                        continue;
-
-                    applied = unite_nested_clusters(inner_cluster_it, *cluster_it, port.first, is_input);
+                    // The inner Buffer can reuse memory of the outer Buffer using `window` sliding only if:
+                    //  - The finalization offset of the latest Loop connected to the inner Buffer is equal to
+                    //    pointer increment of outer Buffer to emulate `window` sliding
+                    //  - This outer Buffer should have the same Buffer ID as inner to move data ptr of inner Buffer after each outer Loop iteration.
+                    //    It's needed because all Loops reset data pointers of connected Buffer after full work.
+                    //    To avoid rewriting of outer Buffer data we have to have the same Buffer ID (GPR) to proportionally shift pointers both Buffers.
+                    if (!can_be_data_ptr_proportionally_shifted(port.second, final_loop_info)) continue;
+
+                    applied = unite_nested_clusters(loop_manager, inner_cluster_it, *cluster_it, port.first, is_input);
                     if (applied) break;
                 }
                 return applied;
@@ -218,101 +226,66 @@ void DefineBufferClusters::parse_nested_loops(const BufferPorts& input_buffers,
     }
 }
 
-int64_t DefineBufferClusters::get_buffer_finalization_offset(const BufferExpressionPtr& buffer_expr) const {
-    auto index = [](const std::vector<PortConnectorPtr>& loop_inputs, const PortConnectorPtr& buffer_out) {
-        const auto it = std::find(loop_inputs.cbegin(), loop_inputs.cend(), buffer_out);
-        OPENVINO_ASSERT(it != loop_inputs.cend(), "Buffer output PortConnector has not been found in target LoopEnd inputs");
-        return std::distance(loop_inputs.cbegin(), it);
+bool DefineBufferClusters::init_buffer_last_loop_port_info(const LoopManagerPtr& loop_manager, const BufferExpressionPtr& buffer_expr,
+                                                           UnifiedLoopInfo::LoopPortInfo& port_info) {
+    auto get_direct_loop_for_buffer_out = [&](const BufferExpressionPtr& buffer_expr, const ExpressionPtr& consumer_expr) -> UnifiedLoopInfoPtr {
+        const auto inner_loops = get_connected_loops(buffer_expr, consumer_expr);
+        if (inner_loops.empty())
+            return nullptr;
+        return loop_manager->get_loop_info<UnifiedLoopInfo>(inner_loops.front());
     };
-    int64_t final_offset = 0;
+
+    bool found = false;
     double last_loop_exec_order = -1 * std::numeric_limits<double>::max();
     const auto& buffer_outs = buffer_expr->get_output_port_connectors();
     for (const auto& buffer_out : buffer_outs) {
         const auto consumers = buffer_out->get_consumers();
         for (const auto& consumer : consumers) {
-            const auto consumer_expr = consumer.get_expr();
-            const auto loop_end = ov::as_type_ptr<ov::snippets::op::LoopEnd>(consumer_expr->get_node());
-            if (loop_end && consumer_expr->get_loop_ids() == buffer_expr->get_loop_ids()) {
-                const auto loop_order = consumer_expr->get_exec_num();
+            if (const auto& direct_loop = get_direct_loop_for_buffer_out(buffer_expr, consumer.get_expr())) {
+                const auto loop_order = direct_loop->get_output_ports().back().expr_port->get_expr()->get_exec_num();
                 if (loop_order > last_loop_exec_order) {
-                    const auto& loop_inputs = consumer_expr->get_input_port_connectors();
-                    final_offset = loop_end->get_finalization_offsets()[index(loop_inputs, buffer_out)];
+                    OPENVINO_ASSERT(direct_loop->is_loop_port(consumer), "Consumer of Buffer from another loop must be loop port");
+                    port_info = direct_loop->get_loop_port_info(consumer);
                     last_loop_exec_order = loop_order;
+                    found = true;
                 }
             }
         }
     }
-    return final_offset;
+    return found;
 }
 
-bool DefineBufferClusters::unite_nested_clusters(const BufferClusters::iterator& inner_cluster_it,
-                                                 BufferCluster& outer_cluster,
-                                                 const BufferExpressionPtr& outer_buffer, bool is_outer_up) {
+bool DefineBufferClusters::unite_nested_clusters(const LoopManagerPtr& loop_manager, const BufferClusters::iterator& inner_cluster_it,
+                                                 BufferCluster& outer_cluster, const BufferExpressionPtr& outer_buffer, bool is_outer_up) {
     for (const auto& inner_buffer : *inner_cluster_it) {
-        ExpressionPtr common_loop_end_expr = nullptr;
-        size_t outer_idx = SIZE_MAX, inner_idx = SIZE_MAX;
-        const auto& up_buffer = is_outer_up ? outer_buffer : inner_buffer;
-        const auto& down_buffer = is_outer_up ? inner_buffer : outer_buffer;
-        auto& up_idx = is_outer_up ? outer_idx : inner_idx;
-        auto& down_idx = is_outer_up ? inner_idx : outer_idx;
-        if (are_buffer_neighbours(up_buffer, down_buffer, common_loop_end_expr, up_idx, down_idx)) {
-            const auto common_loop_end = ov::as_type_ptr<op::LoopEnd>(common_loop_end_expr->get_node());
-            const auto& inner_ptr_increments = common_loop_end->get_ptr_increments();
-            const auto& inner_final_offsets = common_loop_end->get_finalization_offsets();
-            const auto& inner_data_sizes = common_loop_end->get_element_type_sizes();
-            if (SetBufferRegGroup::can_be_in_one_group({ inner_data_sizes[up_idx], inner_ptr_increments[up_idx], inner_final_offsets[up_idx] },
-                                                       { inner_data_sizes[down_idx], inner_ptr_increments[down_idx], inner_final_offsets[down_idx] })) {
-                for (const auto& inner_buffer : *inner_cluster_it)
-                    inner_buffer->set_reg_group(outer_buffer->get_reg_group());
-
-                outer_cluster.insert(inner_cluster_it->cbegin(), inner_cluster_it->cend());
-                m_clusters.erase(inner_cluster_it);
-                return true;
+        const auto& upper_buffer = is_outer_up ? outer_buffer : inner_buffer;
+        const auto& lower_buffer = is_outer_up ? inner_buffer : outer_buffer;
+
+        const auto& lower_buffer_source = lower_buffer->get_input_port_connector(0)->get_source();
+        const auto& upper_buffer_consumers = upper_buffer->get_output_port_connector(0)->get_consumers();
+        for (const auto& upper_buffer_consumer : upper_buffer_consumers) {
+            const auto& connected_loops = get_connected_loops(upper_buffer, upper_buffer_consumer.get_expr());
+            for (const auto& loop_id : connected_loops) {
+                const auto& common_loop_info = loop_manager->get_loop_info<UnifiedLoopInfo>(loop_id);
+                if (!common_loop_info->is_loop_port(lower_buffer_source) || !common_loop_info->is_loop_port(upper_buffer_consumer))
+                    continue;
+
+                const auto upper_port_desc = common_loop_info->get_loop_port_info(upper_buffer_consumer);
+                const auto lower_port_desc = common_loop_info->get_loop_port_info(lower_buffer_source);
+                if (SetBufferRegGroup::can_be_in_one_reg_group(upper_port_desc, lower_port_desc)) {
+                    for (const auto& inner_buffer : *inner_cluster_it)
+                        inner_buffer->set_reg_group(outer_buffer->get_reg_group());
+
+                    add_buffers_to_cluster(outer_cluster, *inner_cluster_it);
+                    m_clusters.erase(inner_cluster_it);
+                    return true;
+                }
             }
         }
     }
     return false;
 }
 
-bool DefineBufferClusters::are_buffer_neighbours(const BufferExpressionPtr& up, const BufferExpressionPtr& down, ExpressionPtr& loop,
-                                                 size_t& up_idx, size_t& down_idx) {
-    auto find_input = [&down](const PortConnectorPtr& in) {
-        return in->get_source().get_expr() == down;
-    };
-    auto find_output = [&down](const PortConnectorPtr& in) {
-        const auto consumers = in->get_consumers();
-        return std::any_of(consumers.cbegin(), consumers.cend(),
-                           [&down](const ExpressionPort& port) { return port.get_expr() == down; });
-    };
-    auto find = [&](const std::vector<PortConnectorPtr>::const_iterator& begin,
-                    const std::vector<PortConnectorPtr>::const_iterator& end,
-                    const std::vector<PortConnectorPtr>::const_iterator& orig_begin,
-                    const ExpressionPort& loop_port,
-                    bool is_input) -> bool {
-        const auto in_buffer_it = is_input ? std::find_if(begin, end, find_input)
-                                           : std::find_if(begin, end, find_output);
-        if (in_buffer_it != end) {
-            up_idx = loop_port.get_index();
-            down_idx = std::distance(orig_begin, in_buffer_it);
-            loop = loop_port.get_expr();
-            return true;
-        }
-        return false;
-    };
-    for (const auto& out : up->get_output_port_connectors()) {
-        for (const auto& buffer_consumer : out->get_consumers()) {
-            const auto buffer_consumer_expr = buffer_consumer.get_expr();
-            const auto loop_end = ov::as_type_ptr<op::LoopEnd>(buffer_consumer_expr->get_node());
-            if (!loop_end)
-                continue;
-            const auto& loop_inputs = buffer_consumer_expr->get_input_port_connectors();
-            if (find(loop_inputs.cbegin(), loop_inputs.cbegin() + loop_end->get_input_num(), loop_inputs.cbegin(), buffer_consumer, true)) return true;
-            if (find(loop_inputs.cbegin() + loop_end->get_input_num(), loop_inputs.cend(), loop_inputs.cbegin(), buffer_consumer, false)) return true;
-        }
-    }
-    return false;
-}
-
 void DefineBufferClusters::parse_memory_access_op(const ExpressionPtr& expr) {
     const auto ma = std::dynamic_pointer_cast<modifier::MemoryAccess>(expr->get_node());
     // TODO: Some full MemoryAccess ops can have inplace inputs and outputs in general.
@@ -340,7 +313,7 @@ bool DefineBufferClusters::run(lowered::LinearIR& linear_ir, lowered::LinearIR::
         const auto& expr = *expr_it;
         const auto op = expr->get_node();
         if (ov::is_type<op::LoopEnd>(op)) {
-            parse_loop(expr_it);
+            parse_loop(linear_ir.get_loop_manager(), expr_it);
             continue;
         }
 
diff --git a/src/common/snippets/src/lowered/pass/mark_invariant_shape_path.cpp b/src/common/snippets/src/lowered/pass/mark_invariant_shape_path.cpp
new file mode 100644
index 00000000000000..b32056d4e32a57
--- /dev/null
+++ b/src/common/snippets/src/lowered/pass/mark_invariant_shape_path.cpp
@@ -0,0 +1,128 @@
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+
+#include "snippets/lowered/pass/mark_invariant_shape_path.hpp"
+
+#include "snippets/lowered/expressions/buffer_expression.hpp"
+#include "snippets/op/memory_access.hpp"
+#include "snippets/snippets_isa.hpp"
+#include "snippets/utils/utils.hpp"
+#include "snippets/itt.hpp"
+
+namespace ov {
+namespace snippets {
+namespace lowered {
+namespace pass {
+
+namespace {
+
+// Specific value to mark ports which doesn't affect output shape of broadcastable ops.
+// For example, ops with output scalar shape or Horizon ops.
+static const size_t NOT_AFFECTING_PATH = SIZE_MAX;
+
+static bool is_shape_broadcastable_op(const ExpressionPtr& expr) {
+    return expr->get_node()->get_autob() != ov::op::AutoBroadcastType::NONE;
+}
+
+static bool is_not_affecting_op(const ExpressionPtr& expr) {
+    const auto& node = expr->get_node();
+    return ov::is_type<ov::snippets::op::HorizonMax>(node) ||
+           ov::is_type<ov::snippets::op::HorizonSum>(node) ||
+           ov::is_type<ov::snippets::op::ReduceMax>(node) ||
+           ov::is_type<ov::snippets::op::ReduceSum>(node) ||
+           ov::is_type<ov::snippets::op::VectorBuffer>(node) ||
+           ov::is_type<ov::snippets::op::BroadcastMove>(node) ||
+           ov::is_type<ov::snippets::op::Scalar>(node);
+}
+
+static bool is_affecting_op(const ExpressionPtr& expr) {
+    const auto& node = expr->get_node();
+    return ov::is_type<ov::snippets::op::Brgemm>(node) ||
+           ov::is_type<ov::snippets::op::Reshape>(node) ||
+           ov::is_type<ov::snippets::op::LoadReshape>(node);
+}
+}  // namespace
+
+size_t MarkInvariantShapePath::getInvariantPortShapePath(const ExpressionPort& port) {
+    auto& rt = get_rt_info(port);
+    const auto rinfo = rt.find("InvariantShapePath");
+    OPENVINO_ASSERT(rinfo != rt.end(), "Invariant path for this expression port has not been marked!");
+    return rinfo->second.as<size_t>();
+}
+
+void MarkInvariantShapePath::SetInvariantPortShapePath(const ExpressionPort& port, size_t value) {
+    OPENVINO_ASSERT(port.get_type() == ExpressionPort::Output, "SetInvariantPortShapePath can be used only for output port");
+    auto& rt = get_rt_info(port);
+    rt["InvariantShapePath"] = value;
+}
+
+ov::RTMap& MarkInvariantShapePath::get_rt_info(const ExpressionPort& port) {
+    const auto& source_port = port.get_type() == ExpressionPort::Input ? port.get_port_connector_ptr()->get_source() : port;
+    const auto& node = source_port.get_expr()->get_node();
+    const auto port_idx = source_port.get_index();
+    OPENVINO_ASSERT(port_idx < node->get_output_size(), "Node has incompatible port count with the expression");
+    return node->output(port_idx).get_rt_info();
+}
+
+bool MarkInvariantShapePath::run(lowered::LinearIR& linear_ir, lowered::LinearIR::constExprIt begin, lowered::LinearIR::constExprIt end) {
+    OV_ITT_SCOPED_TASK(ov::pass::itt::domains::SnippetsTransform, "Snippets::MarkInvariantShapePath");
+
+    bool modified = false;
+
+    // Shape -> color
+    std::map<VectorDims, size_t> colored_shapes;
+
+    size_t color_path = 0;
+
+    auto merge_paths = [&color_path](size_t lhs, size_t rhs) {
+        if (lhs == rhs || rhs == NOT_AFFECTING_PATH) return lhs;
+        if (lhs == NOT_AFFECTING_PATH) return rhs;
+        return ++color_path;
+    };
+
+    for (auto expr_it = begin; expr_it != end; ++expr_it) {
+        const auto& expr = *expr_it;
+        if (ov::is_type<ov::snippets::op::LoopBase>(expr->get_node()))
+            continue;
+
+        for (size_t out_idx = 0; out_idx < expr->get_output_count(); ++out_idx) {
+            const auto& out_shape = expr->get_output_port_descriptor(out_idx)->get_shape();
+            size_t current_color_path;
+            if (colored_shapes.count(out_shape)) {
+                current_color_path = colored_shapes.at(out_shape);
+            } else if (!utils::is_dynamic_vdims(out_shape) && ov::shape_size(out_shape) == 1) {
+                current_color_path = NOT_AFFECTING_PATH;
+            } else {
+                if (is_affecting_op(expr)) {
+                    current_color_path = ++color_path;
+                } else if (is_not_affecting_op(expr)) {
+                    current_color_path = NOT_AFFECTING_PATH;
+                } else if (is_shape_broadcastable_op(expr)) {
+                    current_color_path = NOT_AFFECTING_PATH;
+                    for (size_t in_idx = 0; in_idx < expr->get_input_count(); ++in_idx) {
+                        const auto input_path = getInvariantPortShapePath(expr->get_input_port(in_idx));
+                        current_color_path = merge_paths(current_color_path, input_path);
+                    }
+                } else {
+                    current_color_path = expr->get_input_count() > 0 ? getInvariantPortShapePath(expr->get_input_port(0))
+                                                                     : ++color_path;
+                }
+
+                if (!utils::is_dynamic_vdims(out_shape))
+                    colored_shapes[out_shape] = current_color_path;
+            }
+
+            SetInvariantPortShapePath(expr->get_output_port(out_idx), current_color_path);
+            modified = true;
+        }
+    }
+
+    return modified;
+}
+
+} // namespace pass
+} // namespace lowered
+} // namespace snippets
+} // namespace ov
diff --git a/src/common/snippets/src/lowered/pass/set_buffer_reg_group.cpp b/src/common/snippets/src/lowered/pass/set_buffer_reg_group.cpp
index 9bdb5e8ef3a9dc..46248b9c277818 100644
--- a/src/common/snippets/src/lowered/pass/set_buffer_reg_group.cpp
+++ b/src/common/snippets/src/lowered/pass/set_buffer_reg_group.cpp
@@ -4,8 +4,10 @@
 
 #include "snippets/lowered/pass/set_buffer_reg_group.hpp"
 
+#include "snippets/lowered/pass/mark_invariant_shape_path.hpp"
 #include "snippets/lowered/linear_ir.hpp"
-#include "snippets/snippets_isa.hpp"
+#include "snippets/lowered/loop_manager.hpp"
+#include "snippets/lowered/expressions/buffer_expression.hpp"
 #include "snippets/itt.hpp"
 
 namespace ov {
@@ -19,54 +21,44 @@ inline size_t index(size_t col_num, size_t row, size_t col) {
 }
 } // namespace
 
-bool operator==(const SetBufferRegGroup::ShiftPtrParams& lhs, const SetBufferRegGroup::ShiftPtrParams& rhs) {
-    if (&lhs == &rhs)
-        return true;
-    return lhs.ptr_increment == rhs.ptr_increment && lhs.finalization_offset == rhs.finalization_offset && lhs.data_size == rhs.data_size;
-}
-bool operator!=(const SetBufferRegGroup::ShiftPtrParams& lhs, const SetBufferRegGroup::ShiftPtrParams& rhs) {
-    return !(rhs == lhs);
-}
-
 size_t SetBufferRegGroup::get_buffer_idx(const BufferExpressionPtr& target, const BufferPool& pool) {
     const auto iter = std::find(pool.cbegin(), pool.cend(), target);
     OPENVINO_ASSERT(iter != pool.cend(), "Buffer wasn't find in Buffer system of Subgraph");
     return std::distance(pool.cbegin(), iter);
 }
 
-bool SetBufferRegGroup::can_be_in_one_group(const ShiftPtrParams& lhs, const ShiftPtrParams& rhs) {
-    // If data pointer shift parameters are unknown on model compilation stage (dynamic),
-    // we cannot be sure that these data pointers will be proportionally shifted.
-    // Then we force `false` value here to set unique registers for these buffers
-    const auto are_static = lhs.is_static() && rhs.is_static();
-    const auto equal_ptr_params_shifting = lhs.ptr_increment == rhs.ptr_increment && lhs.finalization_offset == rhs.finalization_offset;
-    const auto equal_element_type_sizes = lhs.data_size == rhs.data_size;
-    return are_static && equal_ptr_params_shifting && (equal_element_type_sizes || (lhs.ptr_increment == 0 && lhs.finalization_offset == 0));
+bool SetBufferRegGroup::can_be_in_one_reg_group(const UnifiedLoopInfo::LoopPortInfo& lhs_info,
+                                                const UnifiedLoopInfo::LoopPortInfo& rhs_info) {
+    const auto equal_element_type_sizes = lhs_info.desc.data_size == rhs_info.desc.data_size;
+    OPENVINO_ASSERT(lhs_info.port.expr_port && rhs_info.port.expr_port, "Expression ports are nullptr!");
+    const auto equal_invariant_shape_paths =
+        MarkInvariantShapePath::getInvariantPortShapePath(*lhs_info.port.expr_port) ==
+        MarkInvariantShapePath::getInvariantPortShapePath(*rhs_info.port.expr_port);
+    const auto equal_is_incremented = lhs_info.port.is_incremented == rhs_info.port.is_incremented;
+    return equal_invariant_shape_paths && equal_is_incremented &&
+           (equal_element_type_sizes || !lhs_info.port.is_incremented || (lhs_info.desc.ptr_increment == 0 && lhs_info.desc.finalization_offset == 0));
 }
 
-bool SetBufferRegGroup::are_adjacent(const std::pair<BufferExpressionPtr, ShiftPtrParams>& lhs,
-                                     const std::pair<BufferExpressionPtr, ShiftPtrParams>& rhs) {
+bool SetBufferRegGroup::are_adjacent(const BufferMap::value_type& lhs, const BufferMap::value_type& rhs) {
     const auto& lhs_ids = lhs.first->get_loop_ids();
     const auto& rhs_ids = rhs.first->get_loop_ids();
     const auto equal_loop_ids = lhs_ids == rhs_ids;
     if (equal_loop_ids) {  // Buffers are connected to the same Loop and have the same outer Loops
-        return !can_be_in_one_group(lhs.second, rhs.second);
+        return !can_be_in_one_reg_group(lhs.second, rhs.second);
     } else {  // Buffers are connected to the same Loop, but one of Buffers - inside this Loop, another - outside
-        // Buffers are adjacent if outer Buffer has not zero data shift params
+        // Buffers are adjacent if outer Buffer has non-zero data shift params
         if (lhs_ids.size() == rhs_ids.size()) // If the count of outer Loops are equal, it means that outer loops are already different
             return true;
         const auto& outer_buffer = lhs_ids.size() < rhs_ids.size() ? lhs : rhs;
         const auto count_outer_loops = std::min(lhs_ids.size(), rhs_ids.size());
         const auto are_outer_loops_the_same = lhs_ids.size() != rhs_ids.size() &&
             std::equal(rhs_ids.cbegin(), rhs_ids.cbegin() + count_outer_loops, lhs_ids.cbegin());
-        const auto outer_buffer_has_zero_shifts = outer_buffer.second.ptr_increment == 0 && outer_buffer.second.finalization_offset == 0;
+        const auto outer_buffer_has_zero_shifts = outer_buffer.second.desc.ptr_increment == 0 && outer_buffer.second.desc.finalization_offset == 0;
         return !(are_outer_loops_the_same && outer_buffer_has_zero_shifts);
     }
 }
 
-void SetBufferRegGroup::update_adj_matrix(const std::pair<BufferExpressionPtr, ShiftPtrParams>& lhs,
-                                          const std::pair<BufferExpressionPtr, ShiftPtrParams>& rhs,
-                                          const BufferPool& buffers,
+void SetBufferRegGroup::update_adj_matrix(const BufferMap::value_type& lhs, const BufferMap::value_type& rhs, const BufferPool& buffers,
                                           std::vector<bool>& adj) {
     const auto size = buffers.size();
     const auto lhs_idx = get_buffer_idx(lhs.first, buffers);
@@ -80,7 +72,8 @@ void SetBufferRegGroup::update_adj_matrix(const std::pair<BufferExpressionPtr, S
     }
 }
 
-std::vector<bool> SetBufferRegGroup::create_adjacency_matrix(LinearIR::constExprIt begin, LinearIR::constExprIt end, const BufferPool& pool) {
+std::vector<bool> SetBufferRegGroup::create_adjacency_matrix(const LoopManagerPtr& loop_manager, LinearIR::constExprIt begin, LinearIR::constExprIt end,
+                                                             const BufferPool& pool) {
     // The sync point to check for adjacency is Loop because only in Loop we increment pointers.
     // So if some Buffers in the one Loop have conflict (cannot be inplace: the different ptr increment and data sizes)
     // they are called as adjacent
@@ -91,10 +84,12 @@ std::vector<bool> SetBufferRegGroup::create_adjacency_matrix(LinearIR::constExpr
 
     for (auto expr_it = begin; expr_it != end; expr_it++) {
         const auto &expr = *expr_it;
-        if (!ov::is_type<op::LoopEnd>(expr->get_node()))
+        const auto& loop_end = ov::as_type_ptr<op::LoopEnd>(expr->get_node());
+        if (!loop_end)
             continue;
 
-        const auto buffer_loop_neighbours = get_buffer_loop_neighbours(expr);
+        const auto& loop_info = loop_manager->get_loop_info<UnifiedLoopInfo>(loop_end->get_id());
+        const auto buffer_loop_neighbours = get_buffer_loop_neighbours(loop_info);
         const auto buffers_loop_inside = get_buffer_loop_inside(expr_it);
         for (auto buffer_it = buffer_loop_neighbours.cbegin(); buffer_it != buffer_loop_neighbours.cend(); ++buffer_it) {
             // If Buffers, that are connected to the same Loop, have not proportionally ptr shift params for this Loop - these Buffers are adjacent
@@ -113,47 +108,33 @@ std::vector<bool> SetBufferRegGroup::create_adjacency_matrix(LinearIR::constExpr
     return adj;
 }
 
-SetBufferRegGroup::BufferMap SetBufferRegGroup::get_buffer_loop_neighbours(const ExpressionPtr& loop_end_expr) {
-    const auto& loop_end = ov::as_type_ptr<op::LoopEnd>(loop_end_expr->get_node());
-    const auto input_count = loop_end->get_input_num();
-    const auto output_count = loop_end->get_output_num();
-
-    const auto& ptr_increments = loop_end->get_ptr_increments();
-    const auto& finalization_offsets = loop_end->get_finalization_offsets();
-    const auto& data_sizes = loop_end->get_element_type_sizes();
-
+SetBufferRegGroup::BufferMap SetBufferRegGroup::get_buffer_loop_neighbours(const UnifiedLoopInfoPtr& loop_info) {
     BufferMap buffer_neighbours;
-    for (size_t i = 0; i < input_count; ++i) {
-        const auto& parent_output = loop_end_expr->get_input_port_connector(i)->get_source().get_expr();
+
+    const auto& loop_inputs = loop_info->get_input_ports_info();
+    for (const auto& port_info : loop_inputs) {
+        const auto& parent_output = port_info.port.expr_port->get_port_connector_ptr()->get_source().get_expr();
         if (const auto buffer_expr = ov::as_type_ptr<BufferExpression>(parent_output)) {
             if (buffer_neighbours.count(buffer_expr) > 0) {
-                OPENVINO_ASSERT(buffer_neighbours[buffer_expr].ptr_increment == ptr_increments[i] &&
-                                buffer_neighbours[buffer_expr].finalization_offset == finalization_offsets[i],
+                const auto& port_desc = port_info.desc;
+                OPENVINO_ASSERT(buffer_neighbours[buffer_expr].desc == port_desc,
                                 "Invalid data pointer shifts: If Buffer has several consumers, this consumers must have the same shifts or zero");
                 continue;
             }
-            buffer_neighbours[buffer_expr] = { data_sizes[i], ptr_increments[i], finalization_offsets[i] };
+            buffer_neighbours[buffer_expr] = port_info;
         }
     }
-    for (size_t i = input_count; i < input_count + output_count; ++i) {
-        // The consumers of the corresponding Store ops
-        const auto consumer_inputs = loop_end_expr->get_input_port_connector(i)->get_consumers();
-        size_t buffer_count = 0;
-        size_t loop_count = 0;
+
+    const auto& loop_outputs = loop_info->get_output_ports_info();
+    for (const auto& port_info : loop_outputs) {
+        const auto& consumer_inputs = port_info.port.expr_port->get_port_connector_ptr()->get_consumers();
         for (const auto& consumer_input : consumer_inputs) {
             const auto& child_expr = consumer_input.get_expr();
-            if (const auto buffer_expr = ov::as_type_ptr<BufferExpression>(child_expr)) {
-                buffer_neighbours[buffer_expr] = { data_sizes[i], ptr_increments[i], finalization_offsets[i] };
-                buffer_count++;
-            } else if (ov::is_type<op::LoopEnd>(child_expr->get_node())) {
-                loop_count++;
-            }
-        }
-        if (buffer_count > 0) {
-            OPENVINO_ASSERT((buffer_count == 1) && (buffer_count + loop_count == consumer_inputs.size()),
-                            "Loop output must have not more than 1 Buffer");
+            if (const auto buffer_expr = ov::as_type_ptr<BufferExpression>(child_expr))
+                buffer_neighbours[buffer_expr] = port_info;
         }
     }
+
     return buffer_neighbours;
 }
 
@@ -164,9 +145,9 @@ SetBufferRegGroup::BufferMap SetBufferRegGroup::get_buffer_loop_inside(const Lin
     for (auto it = std::reverse_iterator<LinearIR::constExprIt>(loop_end_it); (*it)->get_node() != loop_begin; ++it) {
         const auto& inner_expr = *it;
         if (const auto buffer_expr = ov::as_type_ptr<BufferExpression>(inner_expr)) {
-            // Set default zero values since it's not used for adjacency definition in case with Buffers in Loop
+            // Set default value (zeroes) since it's not used for adjacency definition in case with Buffers in Loop
             if (inner_buffers.count(buffer_expr) == 0)
-                inner_buffers[buffer_expr] = { 0, 0, 0 };
+                inner_buffers[buffer_expr] = UnifiedLoopInfo::LoopPortInfo();
         }
     }
     return inner_buffers;
@@ -219,6 +200,7 @@ auto SetBufferRegGroup::coloring(BufferPool& buffers, std::vector<bool>& adj) ->
 
 bool SetBufferRegGroup::run(LinearIR& linear_ir, lowered::LinearIR::constExprIt begin, lowered::LinearIR::constExprIt end) {
     OV_ITT_SCOPED_TASK(ov::pass::itt::domains::SnippetsTransform, "Snippets::SetBufferRegGroup")
+
     // Identify Buffers using Graph coloring algorithm.
     BufferPool buffer_pool = linear_ir.get_buffers();
     // For the better coloring Buffers should be stored in the order of execution numbers
@@ -226,7 +208,7 @@ bool SetBufferRegGroup::run(LinearIR& linear_ir, lowered::LinearIR::constExprIt
               [](const BufferExpressionPtr& lhs, const BufferExpressionPtr& rhs) { return lhs->get_exec_num() < rhs->get_exec_num(); });
 
     // Creation of Adj matrix
-    auto adj = create_adjacency_matrix(begin, end, buffer_pool);
+    auto adj = create_adjacency_matrix(linear_ir.get_loop_manager(), begin, end, buffer_pool);
 
     // Graph coloring algorithm
     const auto color_groups = coloring(buffer_pool, adj);
diff --git a/src/common/snippets/src/pass/mha_tokenization.cpp b/src/common/snippets/src/pass/mha_tokenization.cpp
index c42eb08b82bd4a..beb465ab3a3fbe 100644
--- a/src/common/snippets/src/pass/mha_tokenization.cpp
+++ b/src/common/snippets/src/pass/mha_tokenization.cpp
@@ -268,16 +268,11 @@ ov::snippets::pass::TokenizeMHASnippets::TokenizeMHASnippets(const SnippetsToken
 
         const auto pattern_rank = matmul0->get_output_partial_shape(0).size();
 
-        const auto ops_count_before_softmax = ordered_ops.size();
         auto interm_op = matmul0->get_output_target_inputs(0).begin()->get_node()->shared_from_this();
         // Add supported operations which are between MatMul0 and Softmax to ordered_ops
         if (!update_intermediate_supported_ops(interm_op, ordered_ops, hidden_virtual_ports_count, potential_body_params_count))
             return false;
 
-        // If before Softmax there is Eltwise ops, there will be one more Buffer
-        if (ops_count_before_softmax != ordered_ops.size() && interm_op->get_output_partial_shape(0).rbegin()->is_dynamic())
-            uniqie_buffer_reg_group_count++;
-
         std::shared_ptr<ov::opset1::Reshape> reshape0 = nullptr;
         if (!tokenize_reshape_around_softmax(interm_op, reshape0, ordered_ops))
             return false;
@@ -295,10 +290,6 @@ ov::snippets::pass::TokenizeMHASnippets::TokenizeMHASnippets(const SnippetsToken
         if (axis != rank.get_length() - 1 || interm_op->get_output_target_inputs(0).size() != 1)
             return false;
 
-        // Softmax need one buffer at least
-        if (interm_op->get_output_partial_shape(0).rbegin()->is_dynamic())
-            uniqie_buffer_reg_group_count++;
-
         ordered_ops.push_back(interm_op);
 
         interm_op = interm_op->get_output_target_inputs(0).begin()->get_node()->shared_from_this();
@@ -333,7 +324,7 @@ ov::snippets::pass::TokenizeMHASnippets::TokenizeMHASnippets(const SnippetsToken
         // The Loop will have one Buffer with the same shape both on input and output.
         // Need to check for precision to get if we need one more register for Buffer
         const auto matmul0_prc = op::Brgemm::get_output_type(matmul0->get_input_element_type(0), matmul0->get_input_element_type(1));
-        if (matmul1->get_input_element_type(0).size() != matmul0_prc.size() || matmul1->get_input_partial_shape(0).is_dynamic()) {
+        if (matmul1->get_input_element_type(0).size() != matmul0_prc.size()) {
             uniqie_buffer_reg_group_count++;
         }
 
diff --git a/src/core/include/openvino/op/identity.hpp b/src/core/include/openvino/op/identity.hpp
new file mode 100644
index 00000000000000..a884ba259f0002
--- /dev/null
+++ b/src/core/include/openvino/op/identity.hpp
@@ -0,0 +1,30 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/op/op.hpp"
+
+namespace ov {
+namespace op {
+namespace v16 {
+/// \brief Identity operation is used as a placeholder op.
+///
+/// \ingroup ov_ops_cpp_api
+class OPENVINO_API Identity : public Op {
+public:
+    OPENVINO_OP("Identity", "opset16");
+    Identity() = default;
+    /**
+     * @brief Identity operation is used as a placeholder. It copies the tensor data to the output.
+     */
+    Identity(const Output<Node>& data);
+
+    bool visit_attributes(AttributeVisitor& visitor) override;
+    void validate_and_infer_types() override;
+    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
+};
+}  // namespace v16
+}  // namespace op
+}  // namespace ov
diff --git a/src/core/include/openvino/op/ops.hpp b/src/core/include/openvino/op/ops.hpp
index 135167fe11ed5f..73510a524ef3e1 100644
--- a/src/core/include/openvino/op/ops.hpp
+++ b/src/core/include/openvino/op/ops.hpp
@@ -90,6 +90,7 @@
 #include "openvino/op/hswish.hpp"
 #include "openvino/op/i420_to_bgr.hpp"
 #include "openvino/op/i420_to_rgb.hpp"
+#include "openvino/op/identity.hpp"
 #include "openvino/op/idft.hpp"
 #include "openvino/op/if.hpp"
 #include "openvino/op/interpolate.hpp"
diff --git a/src/core/include/openvino/opsets/opset.hpp b/src/core/include/openvino/opsets/opset.hpp
index 7ab8c43fcec6ab..a05d5dd38d6808 100644
--- a/src/core/include/openvino/opsets/opset.hpp
+++ b/src/core/include/openvino/opsets/opset.hpp
@@ -168,10 +168,15 @@ const OPENVINO_API OpSet& get_opset13();
  */
 const OPENVINO_API OpSet& get_opset14();
 /**
- * @brief Returns map of available opsets
+ * @brief Returns opset15
  * @ingroup ov_opset_cpp_api
  */
 const OPENVINO_API OpSet& get_opset15();
+/**
+ * @brief Returns opset16
+ * @ingroup ov_opset_cpp_api
+ */
+const OPENVINO_API OpSet& get_opset16();
 /**
  * @brief Returns map of available opsets
  * @ingroup ov_opset_cpp_api
diff --git a/src/core/include/openvino/opsets/opset16.hpp b/src/core/include/openvino/opsets/opset16.hpp
new file mode 100644
index 00000000000000..0e2c6c5452f661
--- /dev/null
+++ b/src/core/include/openvino/opsets/opset16.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/op/ops.hpp"
+
+namespace ov {
+namespace opset16 {
+#define _OPENVINO_OP_REG(a, b) using b::a;
+#include "openvino/opsets/opset16_tbl.hpp"
+#undef _OPENVINO_OP_REG
+}  // namespace opset16
+}  // namespace ov
diff --git a/src/core/include/openvino/opsets/opset16_tbl.hpp b/src/core/include/openvino/opsets/opset16_tbl.hpp
new file mode 100644
index 00000000000000..4038aa17b72750
--- /dev/null
+++ b/src/core/include/openvino/opsets/opset16_tbl.hpp
@@ -0,0 +1,17 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#ifndef _OPENVINO_OP_REG
+#    warning "_OPENVINO_OP_REG not defined"
+#    define _OPENVINO_OP_REG(x, y)
+#endif
+
+// Previous opsets operators
+// TODO (ticket: 156877): Add remaining operators from opset15 at the end of opset16 development
+_OPENVINO_OP_REG(Parameter, ov::op::v0)
+_OPENVINO_OP_REG(Convert, ov::op::v0)
+_OPENVINO_OP_REG(ShapeOf, ov::op::v3)
+
+// New operations added in opset16
+_OPENVINO_OP_REG(Identity, ov::op::v16)
diff --git a/src/core/reference/include/openvino/reference/identity.hpp b/src/core/reference/include/openvino/reference/identity.hpp
new file mode 100644
index 00000000000000..7ff48b76560e09
--- /dev/null
+++ b/src/core/reference/include/openvino/reference/identity.hpp
@@ -0,0 +1,26 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <cstring>
+
+namespace ov {
+namespace reference {
+/**
+ * @brief Identity operation computes the identity of the input tensor.
+ *
+ * @param input Input matrix (matrices) pointer.
+ * @param output Output matrix (matrices) pointer.
+ * @param size_in_bytes Size of the input tensor in bytes.
+ **/
+static inline void identity(const char* input, char* output, const size_t size_in_bytes) {
+    if (input == output) {
+        return;
+    } else {
+        std::memcpy(output, input, size_in_bytes);
+    }
+}
+}  // namespace reference
+}  // namespace ov
diff --git a/src/core/src/op/identity.cpp b/src/core/src/op/identity.cpp
new file mode 100644
index 00000000000000..9a18278beca913
--- /dev/null
+++ b/src/core/src/op/identity.cpp
@@ -0,0 +1,44 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/identity.hpp"
+
+#include <cstring>
+
+#include "itt.hpp"
+#include "openvino/core/attribute_visitor.hpp"
+#include "openvino/core/validation_util.hpp"
+#include "openvino/op/util/op_types.hpp"
+#include "openvino/reference/identity.hpp"
+
+namespace ov {
+namespace op {
+namespace v16 {
+
+Identity::Identity(const Output<Node>& data) : Op({data}) {
+    constructor_validate_and_infer_types();
+}
+
+bool Identity::Identity::visit_attributes(AttributeVisitor& visitor) {
+    OV_OP_SCOPE(v16_Identity_visit_attributes);
+    return true;
+}
+
+void Identity::Identity::validate_and_infer_types() {
+    OV_OP_SCOPE(v16_Identity_validate_and_infer_types);
+
+    NODE_VALIDATION_CHECK(this, get_input_size() == 1);
+
+    set_output_type(0, get_input_element_type(0), get_input_partial_shape(0));
+}
+
+std::shared_ptr<Node> Identity::Identity::clone_with_new_inputs(const OutputVector& new_args) const {
+    OV_OP_SCOPE(v16_Identity_clone_with_new_inputs);
+    check_new_args_count(this, new_args);
+
+    return std::make_shared<Identity>(new_args.at(0));
+}
+}  // namespace v16
+}  // namespace op
+}  // namespace ov
diff --git a/src/core/src/opsets/opset.cpp b/src/core/src/opsets/opset.cpp
index ca219f1c68ecd3..f2490010e9dc50 100644
--- a/src/core/src/opsets/opset.cpp
+++ b/src/core/src/opsets/opset.cpp
@@ -113,7 +113,8 @@ const std::map<std::string, std::function<const ov::OpSet&()>>& ov::get_availabl
                                                                                        _OPENVINO_REG_OPSET(opset12),
                                                                                        _OPENVINO_REG_OPSET(opset13),
                                                                                        _OPENVINO_REG_OPSET(opset14),
-                                                                                       _OPENVINO_REG_OPSET(opset15)};
+                                                                                       _OPENVINO_REG_OPSET(opset15),
+                                                                                       _OPENVINO_REG_OPSET(opset16)};
 #undef _OPENVINO_REG_OPSET
     return opset_map;
 }
@@ -288,3 +289,14 @@ const ov::OpSet& ov::get_opset15() {
     });
     return opset;
 }
+
+const ov::OpSet& ov::get_opset16() {
+    static OpSet opset;
+    static std::once_flag flag;
+    std::call_once(flag, [&]() {
+#define _OPENVINO_OP_REG(NAME, NAMESPACE) opset.insert<NAMESPACE::NAME>();
+#include "openvino/opsets/opset16_tbl.hpp"
+#undef _OPENVINO_OP_REG
+    });
+    return opset;
+}
diff --git a/src/core/tests/op.cpp b/src/core/tests/op.cpp
index cf65eecc16cd4c..08fa7a97584e41 100644
--- a/src/core/tests/op.cpp
+++ b/src/core/tests/op.cpp
@@ -67,4 +67,5 @@ TEST(op, opset_multi_thread) {
     doTest(ov::get_opset13);
     doTest(ov::get_opset14);
     doTest(ov::get_opset15);
+    doTest(ov::get_opset16);
 }
diff --git a/src/core/tests/opset.cpp b/src/core/tests/opset.cpp
index 65c79dc9432439..81f6e80c28189f 100644
--- a/src/core/tests/opset.cpp
+++ b/src/core/tests/opset.cpp
@@ -14,6 +14,7 @@
 #include "openvino/opsets/opset13.hpp"
 #include "openvino/opsets/opset14.hpp"
 #include "openvino/opsets/opset15.hpp"
+#include "openvino/opsets/opset16.hpp"
 #include "openvino/opsets/opset2.hpp"
 #include "openvino/opsets/opset3.hpp"
 #include "openvino/opsets/opset4.hpp"
@@ -75,7 +76,8 @@ INSTANTIATE_TEST_SUITE_P(opset,
                                          OpsetTestParams{ov::get_opset12, 178},
                                          OpsetTestParams{ov::get_opset13, 186},
                                          OpsetTestParams{ov::get_opset14, 188},
-                                         OpsetTestParams{ov::get_opset15, 199}),
+                                         OpsetTestParams{ov::get_opset15, 199},
+                                         OpsetTestParams{ov::get_opset16, 4}),
                          OpsetTestNameGenerator{});
 
 class MyOpOld : public ov::op::Op {
diff --git a/src/core/tests/type_prop/identity.cpp b/src/core/tests/type_prop/identity.cpp
new file mode 100644
index 00000000000000..fee04f33ab60f1
--- /dev/null
+++ b/src/core/tests/type_prop/identity.cpp
@@ -0,0 +1,42 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/identity.hpp"
+
+#include <gtest/gtest.h>
+
+#include "common_test_utils/test_assertions.hpp"
+#include "common_test_utils/type_prop.hpp"
+#include "openvino/op/constant.hpp"
+
+using namespace testing;
+
+namespace ov {
+namespace test {
+
+class TypePropIdentityV16Test : public TypePropOpTest<op::v16::Identity> {};
+
+TEST_F(TypePropIdentityV16Test, default_ctor) {
+    const auto data = op::v0::Constant::create(element::f64, Shape{2, 2}, {1.0f, 1.0f, 1.0f, 1.0f});
+    const auto op = make_op();
+    op->set_arguments(OutputVector{data});
+    op->validate_and_infer_types();
+
+    EXPECT_EQ(op->get_input_size(), 1);
+    EXPECT_EQ(op->get_output_size(), 1);
+    EXPECT_EQ(op->get_output_element_type(0), element::f64);
+    EXPECT_EQ(op->get_output_partial_shape(0), PartialShape({2, 2}));
+}
+
+TEST_F(TypePropIdentityV16Test, input_data_ctor) {
+    const auto data = op::v0::Constant::create(element::i64, Shape{1, 2}, {1.0f, 1.0f});
+    const auto op = make_op(data);
+
+    EXPECT_EQ(op->get_input_size(), 1);
+    EXPECT_EQ(op->get_output_size(), 1);
+    EXPECT_EQ(op->get_output_element_type(0), element::i64);
+    EXPECT_EQ(op->get_output_partial_shape(0), PartialShape({1, 2}));
+}
+}  // namespace test
+}  // namespace ov
\ No newline at end of file
diff --git a/src/core/tests/visitors/op/identity.cpp b/src/core/tests/visitors/op/identity.cpp
new file mode 100644
index 00000000000000..f5d66e0b4586ae
--- /dev/null
+++ b/src/core/tests/visitors/op/identity.cpp
@@ -0,0 +1,11 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/identity.hpp"
+
+#include "unary_ops.hpp"
+
+using Type = ::testing::Types<UnaryOperatorType<ov::op::v16::Identity, ov::element::f32>>;
+
+INSTANTIATE_TYPED_TEST_SUITE_P(visitor_without_attribute, UnaryOperatorVisitor, Type, UnaryOperatorTypeName);
diff --git a/src/frontends/common/include/openvino/frontend/extension/op.hpp b/src/frontends/common/include/openvino/frontend/extension/op.hpp
index 55fa919447406a..9022b9f801f800 100644
--- a/src/frontends/common/include/openvino/frontend/extension/op.hpp
+++ b/src/frontends/common/include/openvino/frontend/extension/op.hpp
@@ -25,7 +25,7 @@ inline const ov::OpSet& get_opset_by_name(const std::string& opset_name) {
     if (opsets.find(opset_name) != opsets.end())
         return opsets.at(opset_name)();
     if (opset_name.empty() || opset_name == "latest") {
-        return ov::get_opset15();
+        return ov::get_opset15();  // TODO (ticket: 156877): Update to 16 at the end of opset16 development
     } else {
         FRONT_END_GENERAL_CHECK(false, "Unsupported opset name: ", opset_name);
     }
diff --git a/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.cpp b/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.cpp
index 56c2c75dae9bc2..1c3d283ab673b1 100644
--- a/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.cpp
+++ b/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.cpp
@@ -7,6 +7,9 @@
 #include "snippets/lowered/loop_manager.hpp"
 #include "snippets/utils/utils.hpp"
 
+#ifndef OPENVINO_ARCH_ARM64
+#include "transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.hpp"
+#endif
 namespace ov {
 namespace intel_cpu {
 
@@ -36,10 +39,36 @@ std::string CPURuntimeConfig::to_string() const {
 CPURuntimeConfigurator::CPURuntimeConfigurator() : ov::snippets::RuntimeConfigurator(std::make_shared<CPURuntimeConfig>()) {
 }
 
+void CPURuntimeConfigurator::initialization(const ov::snippets::lowered::LinearIRCPtr& linear_ir) {
+    RuntimeConfigurator::initialization(linear_ir);
+    if (linear_ir->is_dynamic()) {
+        loopPortsAdjuster = BrgemmCopyBLoopPortsAdjuster(linear_ir);
+    }
+}
+
 void CPURuntimeConfigurator::update(const ov::snippets::lowered::LinearIRCPtr& linear_ir) {
-    RuntimeConfigurator::update(linear_ir);
+    m_config->master_shape = linear_ir->get_master_shape();
+    if (linear_ir->is_dynamic()) {
+        update_loop_info(linear_ir);
+    }
+
+    if (!m_optimizer.optimize()) {
+        // If the optimization was not applied, offsets are updated using shapes from descriptors
+        auto shapes = extract_shapes();
+        update_data_offsets(shapes, extract_layouts());
+        m_latest_shapes = std::move(shapes);
+    }
     if (linear_ir->is_dynamic())
+        loopPortsAdjuster.optimize();
+
+    // Update KernelExecutor Table should be before `update_buffer_scratchpad_size`
+    // because `ComputeAllocationSize` depends on subtensors which are updated in the table
+    get_kernel_executor_table()->update_state(linear_ir);
+    update_buffer_scratchpad_size(linear_ir);
+
+    if (linear_ir->is_dynamic()) {
         update_loop_args(linear_ir);
+    }
 }
 
 void CPURuntimeConfigurator::update_tensor_rank(const ov::snippets::VectorDims& master_shape) {
@@ -72,6 +101,40 @@ void CPURuntimeConfigurator::update_loop_args(const ov::snippets::lowered::Linea
         }
     }
 }
+#ifdef OPENVINO_ARCH_ARM64
+CPURuntimeConfigurator::BrgemmCopyBLoopPortsAdjuster::BrgemmCopyBLoopPortsAdjuster(const ov::snippets::lowered::LinearIRCPtr& linear_ir) {
+}
+
+void CPURuntimeConfigurator::BrgemmCopyBLoopPortsAdjuster::optimize() {
+}
+#else
+CPURuntimeConfigurator::BrgemmCopyBLoopPortsAdjuster::BrgemmCopyBLoopPortsAdjuster(const ov::snippets::lowered::LinearIRCPtr& linear_ir) {
+    const auto& pass = std::make_shared<intel_cpu::pass::AdjustBrgemmCopyBLoopPorts>();
+    pass->run(*linear_ir);
+    const auto& affected_uni_loops = pass->get_affected_loops();
+    const auto& loop_map = linear_ir->get_loop_manager()->get_map();
+    for (const auto& p : loop_map) {
+        if (const auto& exp_loop = ov::as_type_ptr<snippets::lowered::ExpandedLoopInfo>(p.second)) {
+            const auto& uni_loop = exp_loop->get_unified_loop_info();
+            if (affected_uni_loops.count(uni_loop))
+                m_affected_uni2exp_map[uni_loop].push_back(exp_loop);
+        }
+    }
+}
+
+void CPURuntimeConfigurator::BrgemmCopyBLoopPortsAdjuster::optimize() {
+    for (const auto& p : m_affected_uni2exp_map) {
+        const auto& uni_loop = p.first;
+        const auto& exp_loops = p.second;
+        snippets::RuntimeConfigurator::LoopInfoRuntimeParamsMap initialized_info;
+        if (intel_cpu::pass::AdjustBrgemmCopyBLoopPorts::update_loop_info(uni_loop)) {
+            initialized_info[uni_loop] = get_loop_runtime_params(uni_loop);
+            for (const auto& exp_loop : exp_loops)
+                update_expanded_loop_info(exp_loop, initialized_info);
+        }
+    }
+}
+#endif
 
 } // namespace intel_cpu
 } // namespace ov
diff --git a/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.hpp b/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.hpp
index 00bc676678d189..d8ef9772e813ff 100644
--- a/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.hpp
+++ b/src/plugins/intel_cpu/src/emitters/snippets/cpu_runtime_configurator.hpp
@@ -44,6 +44,7 @@ class CPURuntimeConfigurator : public ov::snippets::RuntimeConfigurator {
      * @param linear_ir LinearIR
      */
     void init_tensor_rank(const ov::snippets::lowered::LinearIRCPtr& linear_ir) const override;
+    void initialization(const ov::snippets::lowered::LinearIRCPtr& linear_ir) override;
     /**
      * @brief Calculate Loop parameters of Loop emitters and update these values in CPURuntimeConfig
      * @param linear_ir LinearIR
@@ -51,6 +52,18 @@ class CPURuntimeConfigurator : public ov::snippets::RuntimeConfigurator {
     void update_loop_args(const ov::snippets::lowered::LinearIRCPtr& linear_ir) const;
 
     static const size_t rank6D;
+
+    class BrgemmCopyBLoopPortsAdjuster {
+    public:
+        BrgemmCopyBLoopPortsAdjuster() = default;
+        BrgemmCopyBLoopPortsAdjuster(const ov::snippets::lowered::LinearIRCPtr& linear_ir);
+
+        void optimize();
+
+    private:
+        std::unordered_map<snippets::lowered::UnifiedLoopInfoPtr,
+                           std::vector<snippets::lowered::ExpandedLoopInfoPtr>> m_affected_uni2exp_map;
+    } loopPortsAdjuster;
 };
 
 }   // namespace intel_cpu
diff --git a/src/plugins/intel_cpu/src/emitters/snippets/x64/jit_kernel_emitter.cpp b/src/plugins/intel_cpu/src/emitters/snippets/x64/jit_kernel_emitter.cpp
index 4a27c8e17150e8..476123355abe70 100644
--- a/src/plugins/intel_cpu/src/emitters/snippets/x64/jit_kernel_emitter.cpp
+++ b/src/plugins/intel_cpu/src/emitters/snippets/x64/jit_kernel_emitter.cpp
@@ -180,16 +180,16 @@ void jit_kernel_static_emitter::init_data_pointers(const std::vector<Xbyak::Reg6
             h->mov(data_ptr_regs[i], h->ptr[reg_runtime_params + GET_OFF(dst_ptrs) + (i - num_inputs) * sizeof(void*)]);
         init_ptr_with_offset(data_ptr_regs[i], data_offsets[i], reg_tmp);
     }
-    // a rare case when num_params is maximal, so we have no spare gprs
-    // * Static case: we can use reg_runtime_params as the last reg_tmp for the last iteration (and corrupt it), since
-    //     it won't be used anymore
-    // * Dynamic case: we will need reg_runtime_params to pass runtime args to LoopScheduler, so we have to
-    //     push a reg on the stack, and restore it value afterward
+    // A rare case when num_params is maximal, so we have no spare gprs
+    // Note that we need to push-pop runtime params because some kernels might need them even in the static case
+    // (e.g. brgemm emitter for amx tile configuration access)
     if (last_iter_explicitly) {
+        h->push(reg_runtime_params);
         h->mov(data_ptr_regs[i], h->ptr[reg_runtime_params + GET_OFF(dst_ptrs) + (i - num_inputs) * sizeof(void*)]);
         reg_tmp = reg_runtime_params;
         // can corrupt reg_runtime_params, since we won't use it anymore
         init_ptr_with_offset(data_ptr_regs[i], data_offsets[i], reg_tmp);
+        h->pop(reg_runtime_params);
     }
 }
 
diff --git a/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm.cpp b/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm.cpp
index 6f1f4ab93aeda9..fad1be5a5d1289 100644
--- a/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm.cpp
+++ b/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm.cpp
@@ -246,7 +246,7 @@ void BrgemmKernelExecutor::update_config(const ov::snippets::lowered::Expression
         // Note: We check `is_incremented` attribute only for not incremented ports because
         //       this `is_incremented = true` can be changed by `CleanRepeatedDataPointerShifts` optimization
         auto check_port = [&](const ov::snippets::lowered::LoopPort& p) { return p.dim_idx == 0; };
-        OPENVINO_ASSERT(in_ports.size() == 2 && !in_ports.front().is_incremented && std::all_of(in_ports.cbegin(), in_ports.cend(), check_port) &&
+        OPENVINO_ASSERT(in_ports.size() >= 2 && !in_ports.front().is_incremented && std::all_of(in_ports.cbegin(), in_ports.cend(), check_port) &&
                         out_ports.size() == 1 && check_port(out_ports.back()),
                         "Incorrect Loop by Brgemm dimension N");
         N = current_expanded_loop_info->get_increment();
@@ -269,7 +269,7 @@ void BrgemmKernelExecutor::update_config(const ov::snippets::lowered::Expression
         // Quick validation check: Should we check that port is really Brgemm port?
         // Note: We check `is_incremented` attribute only for not incremented ports because
         //       this `is_incremented = true` can be changed by `CleanRepeatedDataPointerShifts` optimization
-        OPENVINO_ASSERT(in_ports.size() == 2 && in_ports.front().dim_idx == 0 && in_ports.back().dim_idx == 1 &&
+        OPENVINO_ASSERT(in_ports.size() >= 2 && in_ports.front().dim_idx == 0 && in_ports.back().dim_idx == 1 &&
                         out_ports.size() == 1 && !out_ports.front().is_incremented,
                         "Incorrect Loop by Brgemm dimension K");
         K = current_expanded_loop_info->get_increment();
@@ -286,7 +286,7 @@ void BrgemmKernelExecutor::update_config(const ov::snippets::lowered::Expression
     OV_CPU_JIT_EMITTER_ASSERT(brgemm_node, "Got invalid node type in update_config");
     // In case of data repacking LDB is chosen in accordance with repacking buffer size
     if (with_repacking(brgemm_node->get_type()))
-        LDB = brgemm_utils::repacking::compute_out_leading_dim(N, brgemm_node->get_input_element_type(1));
+        LDB = brgemm_utils::repacking::compute_LDB(LDB, brgemm_node->get_input_element_type(1));
 
     config.update(DIM_CAST(M), DIM_CAST(N), DIM_CAST(K), LDA, LDB, LDC, beta);
 }
@@ -303,6 +303,8 @@ void BrgemmKernelExecutor::execute(const BrgemmKernelExecutor* executor, call_ar
     }
 
     cpu::x64::brgemm_kernel_params_t brgemm_p;
+    // Note: compensations should be applied only once, so we do it only on the first iteration, when beta == 0
+    size_t is_with_comp = config.get_beta() == 0 && config.is_with_comp();
 
     brgemm_p.batch = nullptr;  // default value
     brgemm_p.ptr_A = args->A;
@@ -311,8 +313,8 @@ void BrgemmKernelExecutor::execute(const BrgemmKernelExecutor* executor, call_ar
     brgemm_p.ptr_D = args->C;
     brgemm_p.ptr_buf = args->scratch;
     brgemm_p.ptr_bias = nullptr;
-    brgemm_p.do_post_ops = static_cast<size_t>(config.is_with_comp());
-    brgemm_p.do_apply_comp = static_cast<size_t>(config.is_with_comp());
+    brgemm_p.do_post_ops = is_with_comp;
+    brgemm_p.do_apply_comp = is_with_comp;
     brgemm_p.skip_accm = 0;
     brgemm_p.BS = 1;  // default value
     OV_CPU_JIT_EMITTER_ASSERT(kernel->compiled_kernel, "has nullptr kernel");
diff --git a/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm_copy_b.cpp b/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm_copy_b.cpp
index 17f8923ae9867b..cc79458c7c4c64 100644
--- a/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm_copy_b.cpp
+++ b/src/plugins/intel_cpu/src/emitters/snippets/x64/kernel_executors/brgemm_copy_b.cpp
@@ -305,7 +305,7 @@ void BrgemmCopyBKernelExecutor::update_config(const ov::snippets::lowered::Expre
     init(N_dim, N_blk, 0);
 
     const auto& brg_weight_etype = expr->get_node()->get_input_element_type(0);
-    const auto LDB = brgemm_utils::repacking::compute_out_leading_dim(N_dim, brg_weight_etype);
+    const auto LDB = brgemm_utils::repacking::compute_LDB(N_dim, brg_weight_etype);
     const auto copy_B_wei_stride = ov::snippets::utils::get_dim_stride(expr->get_input_port(0), config.is_transposed_B() ? 0 : 1) * brg_weight_etype.size();
 
     config.update(N_dim, N_blk, K_dim, K_blk, copy_B_wei_stride, LDB);
diff --git a/src/plugins/intel_cpu/src/nodes/deconv.cpp b/src/plugins/intel_cpu/src/nodes/deconv.cpp
index cb340afc029304..2ee858e730c900 100644
--- a/src/plugins/intel_cpu/src/nodes/deconv.cpp
+++ b/src/plugins/intel_cpu/src/nodes/deconv.cpp
@@ -418,24 +418,38 @@ std::pair<VectorDims, VectorDims> Deconvolution::makeDummyInOutShape() {
     return {inShape.getStaticDims(), outShape.getStaticDims()};
 }
 
-std::vector<memory::format_tag> Deconvolution::getAvailableFormatsForDims(const Shape &dims) const {
-    if (dims.getRank() == 0)
+std::vector<memory::format_tag> Deconvolution::getAvailableFormatsForDims(const Shape& dims) const {
+    if (dims.getRank() == 0) {
         return {memory::format_tag::x};
-    else if (dims.getRank() == 1)
+    } else if (dims.getRank() == 1) {
         return {memory::format_tag::x};
-    else if (dims.getRank() == 2)
+    } else if (dims.getRank() == 2) {
         return {memory::format_tag::nc};
-    else if (dims.getRank() == 3)
-        return {memory::format_tag::ncw,
-                memory::format_tag::nCw8c,
-                memory::format_tag::nCw16c,
-                memory::format_tag::nwc};
-    else if (dims.getRank() == 4)
-        return {memory::format_tag::nchw, memory::format_tag::nChw8c,
-                memory::format_tag::nChw16c, memory::format_tag::nhwc };
-    else if (dims.getRank() == 5)
-        return {memory::format_tag::ncdhw, memory::format_tag::nCdhw8c,
-                memory::format_tag::nCdhw16c, dnnl::memory::format_tag::ndhwc };
+    } else if (dims.getRank() == 3) {
+        // Ticket 156640
+        if (impl::cpu::x64::mayiuse(impl::cpu::x64::avx512_core_amx_fp16)) {
+            return {memory::format_tag::ncw,
+                    memory::format_tag::nCw8c,
+                    memory::format_tag::nCw16c,
+                    memory::format_tag::nwc};
+        } else {
+            return {memory::format_tag::tnc,
+                    memory::format_tag::ntc,
+                    memory::format_tag::ncw,
+                    memory::format_tag::nCw8c,
+                    memory::format_tag::nCw16c};
+        }
+    } else if (dims.getRank() == 4) {
+        return {memory::format_tag::nchw,
+                memory::format_tag::nChw8c,
+                memory::format_tag::nChw16c,
+                memory::format_tag::nhwc};
+    } else if (dims.getRank() == 5) {
+        return {memory::format_tag::ncdhw,
+                memory::format_tag::nCdhw8c,
+                memory::format_tag::nCdhw16c,
+                dnnl::memory::format_tag::ndhwc};
+    }
     return {memory::format_tag::any};
 }
 
diff --git a/src/plugins/intel_cpu/src/nodes/subgraph.cpp b/src/plugins/intel_cpu/src/nodes/subgraph.cpp
index 05a1e5a958771b..ee24dd66493204 100644
--- a/src/plugins/intel_cpu/src/nodes/subgraph.cpp
+++ b/src/plugins/intel_cpu/src/nodes/subgraph.cpp
@@ -17,11 +17,10 @@
 #include "snippets/pass/positioned_pass.hpp"
 #include "snippets/pass/canonicalization.hpp"
 #include "snippets/pass/analyze_broadcastable_inputs.hpp"
-#include "snippets/lowered/linear_ir.hpp"
-#include "snippets/lowered/pass/optimize_domain.hpp"
 #include "snippets/lowered/pass/insert_loops.hpp"
 #include "snippets/lowered/pass/mark_loops.hpp"
 #include "snippets/lowered/pass/insert_buffers.hpp"
+#include "snippets/lowered/pass/init_loops.hpp"
 #include "transformations/defs.hpp"
 #include "transformations/cpu_opset/common/pass/convert_to_swish_cpu.hpp"
 #include "transformations/snippets/common/pass/mul_add_to_fma.hpp"
@@ -38,6 +37,7 @@
 #include "transformations/snippets/x64/pass/brgemm_to_brgemm_cpu.hpp"
 #include "transformations/snippets/x64/pass/enforce_precision.hpp"
 #include "transformations/snippets/x64/shape_inference.hpp"
+#include "transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.hpp"
 #endif
 
 #include "utils/cpu_utils.hpp"
@@ -54,6 +54,7 @@ std::mutex err_print_lock;
 #endif
 
 #ifdef SNIPPETS_LIBXSMM_TPP
+#include "snippets/lowered/pass/optimize_domain.hpp"
 #include "transformations/tpp/x64/pass/brgemm_to_brgemm_tpp.hpp"
 #include "transformations/tpp/x64/pass/eltwise_to_eltwise_tpp.hpp"
 #include "transformations/tpp/x64/pass/scalar_to_scalar_tpp.hpp"
@@ -683,6 +684,10 @@ Subgraph::ControlFlowPasses Subgraph::getControlFlowPasses() const {
 
     SNIPPETS_REGISTER_PASS_RELATIVE(Place::After, ov::snippets::lowered::pass::MarkLoops,
                                     ov::intel_cpu::pass::BrgemmCPUBlocking);
+
+    SNIPPETS_REGISTER_PASS_RELATIVE(Place::After, ov::snippets::lowered::pass::InitLoops,
+                                    ov::intel_cpu::pass::AdjustBrgemmCopyBLoopPorts);
+
     SNIPPETS_REGISTER_PASS_RELATIVE(Place::After, ov::snippets::lowered::pass::InsertLoops,
                                     ov::intel_cpu::pass::FuseLoadStoreConvert);
     SNIPPETS_REGISTER_PASS_RELATIVE(Place::Before, ov::snippets::lowered::pass::InsertBuffers,
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.cpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.cpp
index 844ec338b8a83b..adc215ef1d9900 100644
--- a/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.cpp
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.cpp
@@ -6,7 +6,6 @@
 
 #include "dnnl_extension_utils.h"
 #include "emitters/utils.hpp"
-#include "snippets/utils/utils.hpp"
 #include "transformations/snippets/x64/op/brgemm_copy_b.hpp"
 #include "utils/general_utils.h"
 
@@ -76,10 +75,6 @@ size_t get_elems_in_vec(const ov::element::Type& precision) {
 }
 
 namespace repacking {
-size_t compute_out_leading_dim(const size_t n_block, const ov::element::Type& precision) {
-    return std::max(n_block, compute_inner_n_block(precision));
-}
-
 size_t compute_inner_n_block(const ov::element::Type& precision) {
     switch (precision) {
         case element::i8: return 64;
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.hpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.hpp
index bc627c59920c4b..aeb5b22cd56129 100644
--- a/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.hpp
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/op/brgemm_utils.hpp
@@ -8,6 +8,7 @@
 #include "openvino/core/type/element_type.hpp"
 #include "openvino/core/dimension.hpp"
 #include "snippets/lowered/expression.hpp"
+#include "snippets/utils/utils.hpp"
 
 namespace ov {
 namespace intel_cpu {
@@ -42,14 +43,19 @@ size_t compute_vnni_factor(const ov::element::Type& precision);
 size_t get_elems_in_vec(const ov::element::Type& precision);
 
 namespace repacking {
+/// \brief  Computes inner N block size used by OneDNN implementation. Depends on tensor precision
+size_t compute_inner_n_block(const ov::element::Type& precision);
 /**
  * @brief Computes leading dimension (LDB) which must be used in brgemm and brgemm_copy_b emitters
  * @param n_block N block size shared between BrgemmCPU and BrgemmCopyB node
  * @param precision tensor precision
  */
-size_t compute_out_leading_dim(const size_t n_block, const ov::element::Type& precision);
-/// \brief  Computes inner N block size used by OneDNN implementation. Depends on tensor precision
-size_t compute_inner_n_block(const ov::element::Type& precision);
+template<typename T, typename = typename std::enable_if<(std::is_same<T, size_t>::value || std::is_same<T, int64_t>::value), bool>::type>
+T compute_LDB(T n_block, const ov::element::Type& precision) {
+    return snippets::utils::is_dynamic_value<T>(n_block) ?
+           n_block :
+           std::max(n_block, static_cast<T>(compute_inner_n_block(precision)));
+}
 }   // namespace repacking
 }   // namespace brgemm_utils
 }   // namespace intel_cpu
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.cpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.cpp
new file mode 100644
index 00000000000000..c421e5cc2a4805
--- /dev/null
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.cpp
@@ -0,0 +1,107 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "snippets/itt.hpp"
+
+#include "adjust_brgemm_copy_b_loop_ports.hpp"
+#include "snippets/utils/utils.hpp"
+#include "snippets/lowered/loop_manager.hpp"
+#include "snippets/lowered/expressions/buffer_expression.hpp"
+#include "transformations/snippets/x64/op/brgemm_copy_b.hpp"
+#include "transformations/snippets/x64/op/brgemm_cpu.hpp"
+
+namespace ov {
+namespace intel_cpu {
+
+bool pass::AdjustBrgemmCopyBLoopPorts::update_loop_info(const std::shared_ptr<snippets::lowered::UnifiedLoopInfo>& loop_info) {
+    OPENVINO_ASSERT(loop_info, "Invalid loop info pointer");
+    bool modified = false;
+    auto caller = [&](snippets::lowered::LoopPort &loop_port,
+                      snippets::lowered::UnifiedLoopInfo::LoopPortDesc &loop_desc) {
+        const auto& p = *loop_port.expr_port;
+        if (p.get_type() == snippets::lowered::ExpressionPort::Input &&
+            p.get_index() == 1) {
+            const auto& node = p.get_expr()->get_node();
+            if (auto brg = as_type_ptr<BrgemmCPU>(node)) {
+                const auto precision = node->get_input_element_type(1);
+                /*
+                 * The BrgemmCopyB operation repacks the weights in the following way:
+                 *  1) VNNI format is applied: KN4k for I8/U8, or KN2k for BF16
+                 *  2) Zero padding is applied if N4k < 256 or N2k < 64
+                 */
+                if (brgemm_utils::with_repacking(brg->get_type()) &&
+                    precision != element::f32 && loop_port.is_incremented) {
+                    // K blocking loop: account for zero padding
+                    if (loop_port.dim_idx == 1) {
+                        const auto ptr_incr = loop_desc.ptr_increment;
+                        const auto blocked_shape_ptr_inc = brgemm_utils::repacking::compute_LDB(ptr_incr, precision);
+                        if (ptr_incr != 0 && ptr_incr != blocked_shape_ptr_inc) {
+                            loop_desc.ptr_increment = blocked_shape_ptr_inc;
+                            OPENVINO_ASSERT(loop_desc.finalization_offset % ptr_incr == 0,
+                                            "Can't rescale finalization offsets");
+                            loop_desc.finalization_offset = loop_desc.ptr_increment *
+                                                             (loop_desc.finalization_offset / ptr_incr);
+                        }
+                    // N blocking loop: account for the VNNI format
+                    } else if (loop_port.dim_idx == 0) {
+                        auto k_blk_size = static_cast<int64_t>(brgemm_utils::compute_vnni_factor(precision));
+                        loop_desc.ptr_increment = snippets::utils::dynamic_safe_mul(loop_desc.ptr_increment, k_blk_size);
+                        loop_desc.finalization_offset = snippets::utils::dynamic_safe_mul(loop_desc.finalization_offset, k_blk_size);
+                    } else {
+                        OPENVINO_THROW("Unexpected loop port dimension index in AdjustBrgemmCopyBLoopPorts");
+                    }
+                    modified = true;
+                }
+            }
+        }
+    };
+    loop_info->iterate_through_infos(caller);
+    return modified;
+}
+
+bool pass::AdjustBrgemmCopyBLoopPorts::run(const snippets::lowered::LinearIR& linear_ir) {
+    OV_ITT_SCOPED_TASK(ov::pass::itt::domains::SnippetsTransform, "Snippets::AdjustBrgemmCopyBLoopPorts")
+
+    bool modified = false;
+
+    for (const auto& expr : linear_ir) {
+        const auto& node = expr->get_node();
+        if (!is_type<BrgemmCopyB>(node))
+            continue;
+        const auto& repacking_loop_ids = expr->get_loop_ids();
+        const auto& child_ports = expr->get_output_port(0).get_connected_ports();
+        OPENVINO_ASSERT(child_ports.size() == 1 &&
+                        is_type<snippets::lowered::BufferExpression>(child_ports.begin()->get_expr()),
+                        "BrgemmCopyB should have one BufferExpression child");
+        auto grandchild_ports = child_ports.begin()->get_expr()->get_output_port(0).get_connected_ports();
+        for (const auto& target_port : grandchild_ports) {
+            const auto& port_node = target_port.get_expr()->get_node();
+            if (!is_type<intel_cpu::BrgemmCPU>(port_node)) {
+                OPENVINO_ASSERT(is_type<snippets::op::LoopEnd>(port_node),
+                                "Invalid grandchild of BrgemmCopyB");
+                continue;
+            }
+            const auto &brgemm_loop_ids = target_port.get_expr()->get_loop_ids();
+            // Continue if there is no blocking loop
+            if (brgemm_loop_ids.empty() && repacking_loop_ids.empty())
+                continue;
+            OPENVINO_ASSERT(brgemm_loop_ids.size() > repacking_loop_ids.size(), "Invalid BrgemmCopyB loop configuration");
+            const auto &loop_manager = linear_ir.get_loop_manager();
+            for (auto i = repacking_loop_ids.size(); i < brgemm_loop_ids.size(); i++) {
+                const auto &loop = loop_manager->get_loop_info(brgemm_loop_ids[i]);
+                auto uni_loop = ov::as_type_ptr<snippets::lowered::UnifiedLoopInfo>(loop);
+                if (!uni_loop)
+                    uni_loop = ov::as_type_ptr<snippets::lowered::ExpandedLoopInfo>(loop)->get_unified_loop_info();
+                if (!m_affected_loops.count(uni_loop) && update_loop_info(uni_loop)) {
+                    m_affected_loops.insert(uni_loop);
+                    modified = true;
+                }
+            }
+        }
+    }
+
+    return modified;
+}
+} // namespace intel_cpu
+} // namespace ov
\ No newline at end of file
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.hpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.hpp
new file mode 100644
index 00000000000000..5c65c7a0282823
--- /dev/null
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/adjust_brgemm_copy_b_loop_ports.hpp
@@ -0,0 +1,37 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "snippets/lowered/pass/pass.hpp"
+#include "snippets/lowered/loop_info.hpp"
+
+namespace ov {
+namespace intel_cpu {
+namespace pass {
+
+/**
+ * @interface AdjustBrgemmCopyBLoopPorts
+ * @brief BrgemmCopyB is located outside of blocking loops and repacks input data into a blocked layout.
+ *        This layout should be accounted for when we increment BrgemmCopyB data pointers. This pass
+ *        Finds loop ports connected to BrgemmCopyB and sets appropriate pointer increments.
+  * @ingroup snippets
+ */
+class AdjustBrgemmCopyBLoopPorts: public snippets::lowered::pass::Pass {
+public:
+    AdjustBrgemmCopyBLoopPorts() = default;
+    OPENVINO_RTTI("AdjustBrgemmCopyBLoopPorts", "Pass");
+    bool run(const snippets::lowered::LinearIR& linear_ir);
+    bool run(snippets::lowered::LinearIR& linear_ir) override {
+        return run(const_cast<const snippets::lowered::LinearIR&>(linear_ir));
+    }
+    static bool update_loop_info(const snippets::lowered::UnifiedLoopInfoPtr& uni_loop_info);
+    const std::unordered_set<snippets::lowered::UnifiedLoopInfoPtr>& get_affected_loops() { return m_affected_loops; }
+private:
+    std::unordered_set<snippets::lowered::UnifiedLoopInfoPtr> m_affected_loops;
+};
+
+}  // namespace pass
+}  // namespace intel_cpu
+}  // namespace ov
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.cpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.cpp
index 51565537c43568..9b3009284e09e8 100644
--- a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.cpp
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.cpp
@@ -44,18 +44,6 @@ LinearIR::constExprIt BrgemmCPUBlocking::move_new_memory_buffer(LinearIR& linear
     return std::prev(brgemm_it);
 }
 
-LinearIR::constExprIt BrgemmCPUBlocking::get_loop_begin_pos(LinearIR& linear_ir, const LinearIR::constExprIt& brgemm_it, const ExpressionPtr& copy_b_expr) {
-    auto loop_begin_it = brgemm_it;
-    const auto& brgemm_expr = *brgemm_it;
-    const auto brgemm = ov::as_type_ptr<intel_cpu::BrgemmCPU>(brgemm_expr->get_node());
-    OPENVINO_ASSERT(brgemm, "get_loop_begin_pos must be called only for BrgemmCPU expression");
-    if (with_amx(brgemm->get_type()))
-        loop_begin_it = move_new_memory_buffer(linear_ir, brgemm_it);
-    if (copy_b_expr)
-        loop_begin_it = linear_ir.find(copy_b_expr);
-    return loop_begin_it;
-}
-
 size_t BrgemmCPUBlocking::get_default_n_blk(size_t n) const {
     return dnnl::impl::cpu::x64::mayiuse(dnnl::impl::cpu::x64::avx512_core) ? 64 : 24;
 }
@@ -66,6 +54,8 @@ std::tuple<size_t, size_t, size_t> BrgemmCPUBlocking::get_blocking_params(const
 
     size_t m_blk, n_blk, k_blk;
     std::tie(m_blk, n_blk, k_blk) = BrgemmBlockingBase::get_blocking_params(brgemm_expr);
+    // Note: K,N blocking is functionally enabled, need to turn it on after blocking heuristic is updated to cover
+    // the low precision cases (ticket: 156014)
     if (with_repacking(brgemm->get_type())) {
         n_blk = get_full_dim_value();
         k_blk = get_full_dim_value();
@@ -88,47 +78,48 @@ bool BrgemmCPUBlocking::mark_blocking_loops(LinearIR& linear_ir,
     const auto brgemm = ov::as_type_ptr<ov::intel_cpu::BrgemmCPU>(brgemm_expr->get_node());
     const auto type = brgemm->get_type();
 
-    if (stand_alone(type))
-        return ov::snippets::lowered::pass::BrgemmBlockingBase::mark_blocking_loops(linear_ir, brgemm_it, m_block, n_block, k_block);
+    auto res = ov::snippets::lowered::pass::BrgemmBlockingBase::mark_blocking_loops(linear_ir, brgemm_it, m_block, n_block, k_block);
 
-    brgemm_expr->get_input_port_descriptor(0)->set_subtensor({m_block, k_block});
-    brgemm_expr->get_input_port_descriptor(1)->set_subtensor({k_block, n_block});
-    brgemm_expr->get_output_port_descriptor(0)->set_subtensor({m_block, n_block});
+    if (stand_alone(type))
+        return res;
 
     const auto copy_b_expr = linear_ir.get_expr_by_node(brgemm->get_brgemm_copy());
-    copy_b_expr->get_input_port_descriptor(0)->set_subtensor({k_block, n_block});
-    copy_b_expr->get_output_port_descriptor(0)->set_subtensor({k_block, n_block});
+    const ov::snippets::VectorDims full_subtensor(2, get_full_dim_value());
+    copy_b_expr->get_input_port_descriptor(0)->set_subtensor(full_subtensor);
+    copy_b_expr->get_output_port_descriptor(0)->set_subtensor(full_subtensor);
+
+    if (with_amx(type)) {
+        move_new_memory_buffer(linear_ir, brgemm_it);
+        auto buffer_it = std::prev(brgemm_it);
+        buffer_it->get()->set_loop_ids(brgemm_expr->get_loop_ids());
+    }
+
+    const auto& loop_manager = linear_ir.get_loop_manager();
     if (with_compensations(type)) {
-        const ov::snippets::VectorDims compensations_subtensor{1, n_block};
+        const ov::snippets::VectorDims compensations_subtensor{1, get_full_dim_value()};
         OPENVINO_ASSERT(brgemm_expr->get_input_count() == 3, "Brgemm must have 3 inputs in case of compensations.");
-        brgemm_expr->get_input_port_descriptor(2)->set_subtensor(compensations_subtensor);
+        const auto& compens_port = brgemm_expr->get_input_port(2);
+        compens_port.get_descriptor_ptr()->set_subtensor(compensations_subtensor);
         copy_b_expr->get_output_port_descriptor(1)->set_subtensor(compensations_subtensor);
-    }
 
-    const auto& loop_manager = linear_ir.get_loop_manager();
-    if (!is_full_dim_value(k_block)) {
-        const auto loop_begin = get_loop_begin_pos(linear_ir, brgemm_it, copy_b_expr);
-        const std::vector<LoopPort> entries{LoopPort(brgemm_expr->get_input_port(0), true, 0),
-                                            LoopPort(copy_b_expr->get_input_port(0), true, 1)};
-        const std::vector<LoopPort> exits{LoopPort(brgemm_expr->get_output_port(0), false)};
-        mark_k_blocking(loop_manager, loop_begin, std::next(brgemm_it), entries, exits, k_block);
-    }
-    if (!is_full_dim_value(n_block)) {
-        const auto loop_begin = get_loop_begin_pos(linear_ir, brgemm_it, copy_b_expr);
-        const std::vector<LoopPort> entries{LoopPort(brgemm_expr->get_input_port(0), false),
-                                            LoopPort(copy_b_expr->get_input_port(0), true)};
-        const std::vector<LoopPort> exits{LoopPort(brgemm_expr->get_output_port(0), true)};
-        mark_n_blocking(loop_manager, loop_begin, std::next(brgemm_it), entries, exits, n_block);
-    }
-    if (!is_full_dim_value(m_block)) {
-        const bool include_repacking = !is_full_dim_value(k_block) || !is_full_dim_value(n_block);
-        const auto loop_begin = get_loop_begin_pos(linear_ir, brgemm_it, include_repacking ? copy_b_expr : nullptr);
-        const auto b_input_port = include_repacking ? copy_b_expr->get_input_port(0) : brgemm_expr->get_input_port(1);
-        std::vector<LoopPort> entries{LoopPort(brgemm_expr->get_input_port(0), true), LoopPort(b_input_port, false)};
-        if (!include_repacking && with_compensations(type))
-            entries.emplace_back(brgemm_expr->get_input_port(2), false);
-        const std::vector<LoopPort> exits{LoopPort(brgemm_expr->get_output_port(0), true)};
-        mark_m_blocking(loop_manager, loop_begin, std::next(brgemm_it), entries, exits, m_block);
+        const auto& loop_ids = brgemm_expr->get_loop_ids();
+        size_t i = 0;
+        LoopInfoPtr loop_info = nullptr;
+        auto update_loop_info = [&](LoopPort&& new_port) {
+            OPENVINO_ASSERT(i < loop_ids.size(), "Attempt to access invalid loop id");
+            loop_info = loop_manager->get_loop_info<UnifiedLoopInfo>(loop_ids[i++]);
+            const auto& in_ports = loop_info->get_input_ports();
+            OPENVINO_ASSERT(in_ports.size() > 1, "Invalid number of input loop ports");
+            loop_info->replace_with_new_ports(in_ports[1], {in_ports[1], new_port});
+        };
+        if (!is_full_dim_value(m_block))
+            update_loop_info({compens_port, false, 1});
+
+        if (!is_full_dim_value(n_block))
+            update_loop_info({compens_port, true, 0});
+
+        if (!is_full_dim_value(k_block))
+            update_loop_info({compens_port, false, 1});
     }
     return true;
 }
diff --git a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.hpp b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.hpp
index 22429a6b0c98fb..0fee4e80454f9a 100644
--- a/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.hpp
+++ b/src/plugins/intel_cpu/src/transformations/snippets/x64/pass/lowered/brgemm_cpu_blocking.hpp
@@ -40,10 +40,6 @@ class BrgemmCPUBlocking : public ov::snippets::lowered::pass::BrgemmBlocking<Brg
     static snippets::lowered::LinearIR::constExprIt move_new_memory_buffer(snippets::lowered::LinearIR& linear_ir,
                                                                            const snippets::lowered::LinearIR::constExprIt& brgemm_it);
 
-    static snippets::lowered::LinearIR::constExprIt get_loop_begin_pos(snippets::lowered::LinearIR& linear_ir,
-                                                                       const snippets::lowered::LinearIR::constExprIt& brgemm_it,
-                                                                       const snippets::lowered::ExpressionPtr& copy_b_expr);
-
     snippets::lowered::SpecificIterationHandlers get_k_loop_handlers(size_t work_amount, size_t block_size) const override;
 
     std::tuple<size_t, size_t, size_t> get_blocking_params(const ov::snippets::lowered::ExpressionPtr& brgemm_expr) const override;
diff --git a/src/plugins/intel_cpu/src/transformations/tpp/x64/pass/lowered/set_tpp_leading_dim.cpp b/src/plugins/intel_cpu/src/transformations/tpp/x64/pass/lowered/set_tpp_leading_dim.cpp
index 4f38eddc2bde0f..2a85714a792655 100644
--- a/src/plugins/intel_cpu/src/transformations/tpp/x64/pass/lowered/set_tpp_leading_dim.cpp
+++ b/src/plugins/intel_cpu/src/transformations/tpp/x64/pass/lowered/set_tpp_leading_dim.cpp
@@ -16,13 +16,6 @@ namespace tpp {
 namespace pass {
 namespace {
 using ExpressionPort = snippets::lowered::ExpressionPort;
-bool is_planar_layout(const std::vector<size_t>& layout) {
-    for (size_t i = 0; i < layout.size(); i++) {
-        if (layout[i] != i)
-            return false;
-    }
-    return true;
-}
 // Note: Buffer is directly connected to the port if it remains in the same loops with the port's expression
 //  Directly connected Buffers store data densely, so strides are defined by subternsor dims
 //  Indirectly connected Buffers (with loops between the expr and Buffer) store data according
@@ -81,12 +74,12 @@ size_t get_leading_dim(ExpressionPort port, const snippets::lowered::LoopManager
             subtensor[idx] = shape[shape.size() - i];
         }
     }
-    OPENVINO_ASSERT(!full_dim_substituted || is_planar_layout(layout),
+    OPENVINO_ASSERT(!full_dim_substituted || ov::snippets::utils::is_planar_layout(layout),
                     "Only planar layouts are supported for FULL_DIM substitution");
 
     if (has_directly_connected_buffer(port, loop_mngr)) {
         shape = port_desc->get_subtensor();
-        OPENVINO_ASSERT(is_planar_layout(layout), "Only planar layouts are supported for Buffers");
+        OPENVINO_ASSERT(ov::snippets::utils::is_planar_layout(layout), "Only planar layouts are supported for Buffers");
         const auto rank_diff = static_cast<int64_t>(layout.size()) - static_cast<int64_t>(shape.size());
         if (rank_diff > 0)
             layout.erase(layout.end() - rank_diff, layout.end());
diff --git a/src/plugins/intel_cpu/tests/functional/custom/subgraph_tests/src/common/concat_transpose_sdp_transpose.cpp b/src/plugins/intel_cpu/tests/functional/custom/subgraph_tests/src/common/concat_transpose_sdp_transpose.cpp
index bbfe619f3f0c35..65bc379c78b540 100644
--- a/src/plugins/intel_cpu/tests/functional/custom/subgraph_tests/src/common/concat_transpose_sdp_transpose.cpp
+++ b/src/plugins/intel_cpu/tests/functional/custom/subgraph_tests/src/common/concat_transpose_sdp_transpose.cpp
@@ -361,7 +361,7 @@ class ConcatSDPTransposeTestSetState : public ConcatSDPTransposeTestBase {
             val += 0.13f;
 
             state.set_state(new_state);
-    }
+        }
     }
     std::vector<ov::Tensor> run_test(std::shared_ptr<ov::Model> model) {
         function = model;
diff --git a/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/brgemm_blocking.cpp b/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/brgemm_blocking.cpp
index 89f2e06c14a9fa..738afba6a101f9 100644
--- a/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/brgemm_blocking.cpp
+++ b/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/brgemm_blocking.cpp
@@ -81,43 +81,6 @@ void create_brgemm_loop_infos(const LinearIRPtr& linear_ir,
                 BrgemmBlockingBase::get_default_blocking_loop_handlers(m, m_block)));
     }
 }
-
-void create_brgemm_with_copy_b_loop_infos(const LinearIRPtr& linear_ir,
-                                          const ExpressionPtr& brgemm_expr,
-                                          const ExpressionPtr& copy_b_expr,
-                                          size_t m = 0, size_t m_blk = 0,
-                                          size_t k = 0, size_t k_blk = 0,
-                                          size_t n = 0, size_t n_blk = 0) {
-    const bool k_block = k != 0 && k_blk != 0;
-    const bool n_block = k != 0 && k_blk != 0;
-    const bool m_block = m != 0 && m_blk != 0;
-    if (k_block) {
-        const auto loop_info =
-            std::make_shared<ov::snippets::lowered::UnifiedLoopInfo>(k, k_blk,
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_input_port(0)),
-                                      LoopPort(copy_b_expr->get_input_port(0), true, 1)},
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_output_port(0), false)},
-                get_k_loop_handlers(k, k_block));
-        linear_ir->get_loop_manager()->add_loop_info(loop_info);
-    }
-    if (n_block) {
-        linear_ir->get_loop_manager()->add_loop_info(
-            std::make_shared<ov::snippets::lowered::UnifiedLoopInfo>(n, n_blk,
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_input_port(0), false),
-                                      LoopPort(copy_b_expr->get_input_port(0))},
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_output_port(0))},
-                BrgemmBlockingBase::get_default_blocking_loop_handlers(n, n_block)));
-    }
-    if (m_block) {
-        const auto& second_input_port = k_block || n_block ? copy_b_expr->get_input_port(0) : brgemm_expr->get_input_port(1);
-        linear_ir->get_loop_manager()->add_loop_info(
-            std::make_shared<ov::snippets::lowered::UnifiedLoopInfo>(m, m_blk,
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_input_port(0), true, 1),
-                                      LoopPort(second_input_port, false, 1)},
-                std::vector<LoopPort>{LoopPort(brgemm_expr->get_output_port(0), true, 1)},
-                BrgemmBlockingBase::get_default_blocking_loop_handlers(m, m_block)));
-    }
-}
 } // namespace
 
 class BrgemmBlockingTest : public LoweredPassTestsF {
@@ -230,6 +193,8 @@ TEST_F(BrgemmCPUBlockingTest, BlockingIsNotNeeded) {
 }
 
 TEST_F(BrgemmCPUBlockingTest, WithDataRepacking) {
+    // Skipped because K,N blocking is disabled until heuristic is updated (ticket: 156014)
+    GTEST_SKIP();
     const ov::Dimension::value_type m = 384;
     const ov::Dimension::value_type k = 1024;
     const ov::Dimension::value_type n = 384;
@@ -257,14 +222,16 @@ TEST_F(BrgemmCPUBlockingTest, WithDataRepacking) {
 
         auto brgemm = linear_ir_ref->push_node<BrgemmCPU>(data_a.second, copy_b.second, BRGEMM_TYPE::REPACKING_ONLY);
         const auto& brgemm_expr = *brgemm.first;
-        init_expr_descriptors(brgemm_expr, {{m_blk, full_dim}, {full_dim, full_dim}, {m_blk, full_dim}});
-        create_brgemm_with_copy_b_loop_infos(linear_ir_ref, brgemm_expr, copy_b_expr, m, m_blk);
-        brgemm_expr->set_loop_ids({0});
+        init_expr_descriptors(brgemm_expr, {{m_blk, k_blk}, {k_blk, n_blk}, {m_blk, n_blk}});
+        create_brgemm_loop_infos(linear_ir_ref, brgemm_expr, m, m_blk, k, k_blk, n, n_blk);
+        brgemm_expr->set_loop_ids({2, 1, 0});
         auto result = linear_ir_ref->push_node<ov::opset10::Result>(brgemm.second);
     }
 }
 
 TEST_F(BrgemmCPUBlockingTest, WithCompensations) {
+    // Skipped because K,N blocking is disabled until heuristic is updated (ticket: 156014)
+    GTEST_SKIP();
     const ov::Dimension::value_type m = 384;
     const ov::Dimension::value_type k = 1024;
     const ov::Dimension::value_type n = 384;
@@ -292,14 +259,27 @@ TEST_F(BrgemmCPUBlockingTest, WithCompensations) {
         const auto& copy_b_n = copy_b.second;
         auto brgemm = linear_ir_ref->push_node<BrgemmCPU>(data_a.second, copy_b_n->output(0), copy_b_n->output(1), BRGEMM_TYPE::WITH_COMPENSATIONS);
         const auto& brgemm_expr = *brgemm.first;
-        init_expr_descriptors(brgemm_expr, {{m_blk, full_dim}, {full_dim, full_dim}, {1, full_dim}, {m_blk, full_dim}});
-        create_brgemm_loop_infos(linear_ir_ref, brgemm_expr, m, m_blk);
-        brgemm_expr->set_loop_ids({0});
+        init_expr_descriptors(brgemm_expr, {{m_blk, k_blk}, {k_blk, n_blk}, {1, full_dim},  {m_blk, n_blk}});
+        create_brgemm_loop_infos(linear_ir_ref, brgemm_expr, m, m_blk, k, k_blk, n, n_blk);
+
+        const auto loop_manager = linear_ir_ref->get_loop_manager();
+        auto update_loop_info = [&loop_manager](size_t loop_id, LoopPort&& new_port) {
+            const auto& loop_info = loop_manager->get_loop_info<UnifiedLoopInfo>(loop_id);
+            const auto& in_ports = loop_info->get_input_ports();
+            loop_info->replace_with_new_ports(in_ports[1], {in_ports[1], new_port});
+        };
+        const auto& compens_port = brgemm_expr->get_input_port(2);
+        update_loop_info(1, {compens_port, true, 0});
+        update_loop_info(0, {compens_port, false, 1});
+
+        brgemm_expr->set_loop_ids({2, 1, 0});
         auto result = linear_ir_ref->push_node<ov::opset10::Result>(brgemm.second);
     }
 }
 
 TEST_F(BrgemmCPUBlockingTest, AMX) {
+    // Skipped because K,N blocking is disabled until heuristic is updated (ticket: 156014)
+    GTEST_SKIP();
     const ov::Dimension::value_type m = 384;
     const ov::Dimension::value_type k = 1024;
     const ov::Dimension::value_type n = 384;
@@ -322,16 +302,25 @@ TEST_F(BrgemmCPUBlockingTest, AMX) {
         auto data_b = linear_ir_ref->push_node<ov::opset10::Parameter>(precision, input_shape_b);
         auto copy_b = linear_ir_ref->push_node<BrgemmCopyB>(data_b.second, precision, BRGEMM_TYPE::REPACKING_ONLY);
         const auto copy_b_expr = *copy_b.first;
-        init_expr_descriptors(copy_b_expr, {{full_dim, full_dim}, {full_dim, full_dim}});
+        init_expr_descriptors(copy_b_expr, {{full_dim, full_dim},
+                                            {full_dim, full_dim}});
 
-        auto scratch = linear_ir_ref->push_node<snippets::op::Buffer>(ov::Shape{BrgemmCPU::SCRATCH_BYTE_SIZE});
-        scratch.first->get()->set_loop_ids({0});
+        auto scratch = linear_ir_ref->push_node<snippets::op::Buffer>(ov::Shape {BrgemmCPU::SCRATCH_BYTE_SIZE});
+        scratch.first->get()->set_loop_ids({2, 1, 0});
 
-        auto brgemm = linear_ir_ref->push_node<BrgemmCPU>(data_a.second, copy_b.second, scratch.second, BRGEMM_TYPE::WITH_AMX);
+        auto brgemm = linear_ir_ref->push_node<BrgemmCPU>(data_a.second, copy_b.second, scratch.second,
+                                                          BRGEMM_TYPE::WITH_AMX);
         const auto& brgemm_expr = *brgemm.first;
-        init_expr_descriptors(brgemm_expr, {{m_blk, full_dim}, {full_dim, full_dim}, get_default_subtensor(), {m_blk, full_dim}});
-        create_brgemm_with_copy_b_loop_infos(linear_ir_ref, brgemm_expr, copy_b_expr, m, m_blk);
-        brgemm_expr->set_loop_ids({0});
+        init_expr_descriptors(brgemm_expr, {{m_blk, k_blk}, {k_blk, n_blk}, get_default_subtensor(), {m_blk, n_blk}});
+        create_brgemm_loop_infos(linear_ir_ref, brgemm_expr, m, 0, k, k_blk, n, n_blk);
+
+        std::vector<LoopPort> entries {LoopPort(brgemm_expr->get_input_port(0), true, 1),
+                                       LoopPort(brgemm_expr->get_input_port(1), false, 1)};
+        std::vector<LoopPort> exits {LoopPort(brgemm_expr->get_output_port(0), true, 1)};
+        auto handlers = BrgemmBlockingBase::get_default_blocking_loop_handlers(m, m_blk);
+        linear_ir_ref->get_loop_manager()->
+            add_loop_info(std::make_shared<ov::snippets::lowered::UnifiedLoopInfo>(m, m_blk, entries, exits, handlers));
+        brgemm_expr->set_loop_ids({2, 1, 0});
         auto result = linear_ir_ref->push_node<ov::opset10::Result>(brgemm.second);
     }
 }
diff --git a/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/buffer_allocation.cpp b/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/buffer_allocation.cpp
index 6dad1d4772f531..e31a8bebb95758 100644
--- a/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/buffer_allocation.cpp
+++ b/src/plugins/intel_cpu/tests/unit/snippets_transformations/x64/lowered/buffer_allocation.cpp
@@ -36,21 +36,24 @@ using BRGEMM_TYPE = intel_cpu::brgemm_utils::BRGEMM_TYPE;
  */
 
 typedef std::tuple<
-    bool,   // Optimized pipeline
-    bool,   // With SplitLoops opt
-    size_t, // Expected Buffer size in bytes
-    size_t, // Expected unique Buffer reg group count
-    size_t  // Expected unique Buffer cluster count
+    std::vector<ov::PartialShape>, // Input shapes
+    bool,                          // Optimized pipeline
+    bool,                          // With SplitLoops opt
+    size_t,                        // Expected Buffer size in bytes
+    size_t,                        // Expected unique Buffer reg group count
+    size_t                         // Expected unique Buffer cluster count
 > BufferAllocationCPUParams;
 
 class BufferAllocationCPUTest : public testing::TestWithParam<BufferAllocationCPUParams> {
 public:
     using VectorDims = ov::snippets::VectorDims;
     static std::string getTestCaseName(testing::TestParamInfo<BufferAllocationCPUParams> obj) {
+        std::vector<ov::PartialShape> shapes;
         bool is_optimized, with_split_loops;
         size_t expected_size, expected_reg_group_count, expected_cluster_count;
-        std::tie(is_optimized, with_split_loops, expected_size, expected_reg_group_count, expected_cluster_count) = obj.param;
+        std::tie(shapes, is_optimized, with_split_loops, expected_size, expected_reg_group_count, expected_cluster_count) = obj.param;
         std::ostringstream result;
+        result << "Shapes=" << ov::test::utils::partialShape2str(shapes) << "_";
         result << "Opt=" << ov::test::utils::bool2str(is_optimized) << "_";
         result << "Split=" << ov::test::utils::bool2str(with_split_loops) << "_";
         result << "ExpBufferSize=" << expected_size << "_";
@@ -61,9 +64,11 @@ class BufferAllocationCPUTest : public testing::TestWithParam<BufferAllocationCP
 
 protected:
     void SetUp() override {
-        std::tie(m_is_buffer_optimized, m_with_split_loops, m_expected_size, m_expected_reg_group_count, m_expected_cluster_count) = this->GetParam();
+        std::vector<ov::PartialShape> shapes;
+        std::tie(shapes, m_is_buffer_optimized, m_with_split_loops, m_expected_size,
+                 m_expected_reg_group_count, m_expected_cluster_count) = this->GetParam();
 
-        const auto body = GetModel();
+        const auto body = GetModel(shapes);
         m_linear_ir = ov::snippets::lowered::LinearIR(body, std::make_shared<ov::snippets::CPUShapeInferSnippetsFactory>());
         m_linear_ir.set_loop_depth(m_loop_depth);
         // When Subgraph::control_flow_transformations become public method,
@@ -105,7 +110,7 @@ class BufferAllocationCPUTest : public testing::TestWithParam<BufferAllocationCP
         EXPECT_EQ(m_linear_ir.get_static_buffer_scratchpad_size(), m_expected_size);
     }
 
-    virtual std::shared_ptr<ov::Model> GetModel() const = 0;
+    virtual std::shared_ptr<ov::Model> GetModel(const std::vector<ov::PartialShape>& shapes) const = 0;
 
     void MarkOp(const std::shared_ptr<ov::Node>& node, const std::vector<size_t>& subtensor) const {
         for (const auto& input : node->inputs())
@@ -131,20 +136,16 @@ class BufferAllocationCPUTest : public testing::TestWithParam<BufferAllocationCP
 
 class MHAFP32BufferAllocationTest : public BufferAllocationCPUTest {
 protected:
-    std::shared_ptr<ov::Model> GetModel() const override {
+    std::shared_ptr<ov::Model> GetModel(const std::vector<ov::PartialShape>& shapes) const override {
         const auto subtensor_scalar = std::vector<size_t>{1};
         const auto subtensor_power = std::vector<size_t>{1, ov::snippets::utils::get_full_dim_value()};
         const auto subtensor_full = std::vector<size_t>(2, ov::snippets::utils::get_full_dim_value());
 
         // Dims are selected in order to have blocking loops by each dim
-        const size_t m = 1024;
-        const size_t k = 1024;
-        const size_t n1 = 128;
-        const size_t n2 = 256;
-
-        const auto parameter0 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, ov::PartialShape({1, 12, m, k}));
-        const auto parameter1 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, ov::PartialShape({1, n1, 12, k}));
-        const auto parameter2 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, ov::PartialShape({1, 12, n1, n2}));
+        OPENVINO_ASSERT(shapes.size() == 3, "Incorrect count of input shapes");
+        const auto parameter0 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, shapes[0]);
+        const auto parameter1 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, shapes[1]);
+        const auto parameter2 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, shapes[2]);
 
         const auto order = std::vector<size_t>{0, 2, 3, 1};
         const auto load_reshape = std::make_shared<ov::snippets::op::LoadReshape>(parameter1, 1, 0, order);
@@ -186,20 +187,15 @@ class MHAFP32BufferAllocationTest : public BufferAllocationCPUTest {
 
 class MHABF16AMXBufferAllocationTest : public BufferAllocationCPUTest {
 protected:
-    std::shared_ptr<ov::Model> GetModel() const override {
+    std::shared_ptr<ov::Model> GetModel(const std::vector<ov::PartialShape>& shapes) const override {
         const auto subtensor_scalar = std::vector<size_t>{1};
         const auto subtensor_power = std::vector<size_t>{1, ov::snippets::utils::get_full_dim_value()};
         const auto subtensor_full = std::vector<size_t>(2, ov::snippets::utils::get_full_dim_value());
 
-        // Dims are selected in order to have blocking loops by each dim
-        const size_t m = 1024;
-        const size_t k = 1024;
-        const size_t n1 = 128;
-        const size_t n2 = 256;
-
-        const auto parameter0 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, ov::PartialShape({1, 12, m, k}));
-        const auto parameter1 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, ov::PartialShape({1, n1, 12, k}));
-        const auto parameter2 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, ov::PartialShape({1, 12, n1, n2}));
+        OPENVINO_ASSERT(shapes.size() == 3, "Incorrect count of input shapes");
+        const auto parameter0 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, shapes[0]);
+        const auto parameter1 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, shapes[1]);
+        const auto parameter2 = std::make_shared<ov::op::v0::Parameter>(ov::element::bf16, shapes[2]);
 
         const auto order = std::vector<size_t>{0, 2, 3, 1};
         const auto load_reshape = std::make_shared<ov::snippets::op::LoadReshape>(parameter1, 1, 0, order);
@@ -264,8 +260,17 @@ TEST_P(MHABF16AMXBufferAllocationTest, BufferAllocationCPU) {
 
 namespace BufferAllocationCPUTest_Instances {
 
+std::vector<ov::PartialShape> static_shapes = {
+    { 1, 12, 1024, 1024 }, {1, 128, 12, 1024 }, {1, 12, 128, 256 },
+};
+
+std::vector<ov::PartialShape> dynamic_shapes = {
+    { -1, -1, -1, -1 }, { -1, -1, -1, -1 }, { -1, -1, -1, -1 },
+};
+
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHANotOptimizedWSplit, MHAFP32BufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(false),
                                  ::testing::Values(true),
                                  ::testing::Values(591360), // Each Buffer has own allocated memory
@@ -275,6 +280,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHANotOptimizedWSplit,
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHAOptimizedWSplit, MHAFP32BufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(true),
                                  ::testing::Values(true),
                                  ::testing::Values(573440), // (Buffer before brgemm) + (between brgemms) + (after brgemm)
@@ -284,6 +290,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHAOptimizedWSplit, MHA
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHANotOptimizedWOSplit, MHAFP32BufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(false),
                                  ::testing::Values(false),
                                  ::testing::Values(2622976), // Each Buffer has own allocated memory
@@ -293,6 +300,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHANotOptimizedWOSplit,
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHAOptimizedWOSplit, MHAFP32BufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(true),
                                  ::testing::Values(false),
                                  ::testing::Values(1572864), // (between brgemms) + (Buffer before brgemm0 and after brgemm1)
@@ -302,6 +310,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHAOptimizedWOSplit, MH
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXNotOptimizedWSplit, MHABF16AMXBufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(false),
                                  ::testing::Values(true),
                                  ::testing::Values(713984),
@@ -311,15 +320,17 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXNotOptimizedW
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXOptimizedWSplit, MHABF16AMXBufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(true),
                                  ::testing::Values(true),
                                  ::testing::Values(524288),
                                  ::testing::Values(3),
-                                 ::testing::Values(8)),
+                                 ::testing::Values(7)),
                          BufferAllocationCPUTest::getTestCaseName);
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXNotOptimizedWOSplit, MHABF16AMXBufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(false),
                                  ::testing::Values(false),
                                  ::testing::Values(2491648),
@@ -329,11 +340,32 @@ INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXNotOptimizedW
 
 INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXOptimizedWOSplit, MHABF16AMXBufferAllocationTest,
                          ::testing::Combine(
+                                 ::testing::Values(static_shapes),
                                  ::testing::Values(true),
                                  ::testing::Values(false),
-                                 ::testing::Values(1409024),
+                                 ::testing::Values(1671168),
+                                 ::testing::Values(3),
+                                 ::testing::Values(7)),
+                         BufferAllocationCPUTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHAOptimizedWSplit_Dynamic, MHAFP32BufferAllocationTest,
+                         ::testing::Combine(
+                                 ::testing::Values(dynamic_shapes),
+                                 ::testing::Values(true),
+                                 ::testing::Values(true),
+                                 ::testing::Values(0),  // no static clusters
+                                 ::testing::Values(2),  // (Buffer before brgemm0 and after brgemm1) + (between brgemms)
+                                 ::testing::Values(3)), // (Buffer before brgemm0) + (between brgemms) + (after brgemm1)
+                         BufferAllocationCPUTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Snippets_BufferAllocation_MHABF16AMXOptimizedWSplit_Dynamic, MHABF16AMXBufferAllocationTest,
+                         ::testing::Combine(
+                                 ::testing::Values(dynamic_shapes),
+                                 ::testing::Values(true),
+                                 ::testing::Values(true),
+                                 ::testing::Values(32768),  // only WSP buffers
                                  ::testing::Values(3),
-                                 ::testing::Values(8)),
+                                 ::testing::Values(7)),
                          BufferAllocationCPUTest::getTestCaseName);
 
 }  // namespace BufferAllocationCPUTest_Instances
diff --git a/src/plugins/intel_gpu/include/intel_gpu/primitives/one_hot.hpp b/src/plugins/intel_gpu/include/intel_gpu/primitives/one_hot.hpp
index c66bbedc80ee0c..d47a128c62c434 100644
--- a/src/plugins/intel_gpu/include/intel_gpu/primitives/one_hot.hpp
+++ b/src/plugins/intel_gpu/include/intel_gpu/primitives/one_hot.hpp
@@ -54,6 +54,21 @@ struct one_hot : public primitive_base<one_hot> {
         , on_value(on_value)
         , off_value(off_value) {}
 
+    /// @brief onehot with depth from Select node
+    one_hot(const primitive_id& id,
+            const input_info& input,
+            const input_info& input_depth,
+            const tensor& shape,
+            const data_types output_dt,
+            const int64_t& one_hot_axis,
+            const float& on_value = 1.0f,
+            const float& off_value = 0.0f)
+        : primitive_base(id, {input, input_depth}, 1, {optional_data_type{output_dt}})
+        , shape(shape)
+        , one_hot_axis(one_hot_axis)
+        , on_value(on_value)
+        , off_value(off_value) {}
+
     /// @brief Constructs one-hot primitive layer.
     /// @param id              An identifier of new primitive.
     /// @param input           An identifier of primitive which is an input for newly created one-hot primitive.
diff --git a/src/plugins/intel_gpu/src/graph/include/one_hot_inst.h b/src/plugins/intel_gpu/src/graph/include/one_hot_inst.h
index 782751e261e51a..2e5dc81a3d4049 100644
--- a/src/plugins/intel_gpu/src/graph/include/one_hot_inst.h
+++ b/src/plugins/intel_gpu/src/graph/include/one_hot_inst.h
@@ -22,7 +22,7 @@ struct typed_program_node<one_hot> : typed_program_node_base<one_hot> {
         support_padding_all(true);
     }
     program_node& input() const { return get_dependency(0); }
-    std::vector<size_t> get_shape_infer_dependencies() const override { return {}; }
+    std::vector<size_t> get_shape_infer_dependencies() const override { return {1}; }
 };
 
 using one_hot_node = typed_program_node<one_hot>;
diff --git a/src/plugins/intel_gpu/src/graph/one_hot.cpp b/src/plugins/intel_gpu/src/graph/one_hot.cpp
index ede34e8e0935b0..bb90e3bf1276b5 100644
--- a/src/plugins/intel_gpu/src/graph/one_hot.cpp
+++ b/src/plugins/intel_gpu/src/graph/one_hot.cpp
@@ -66,11 +66,23 @@ std::vector<layout> one_hot_inst::calc_output_layouts(const one_hot_node& /*node
     };
 
     int64_t depth = desc->depth;
+    auto& memory_deps = impl_param.memory_deps;
+
+    std::unordered_map<size_t, ov::Tensor> const_data = {};
+    if (depth != 0) {
+        auto depth_tensor = ov::Tensor(ov::element::i64, ov::Shape{1}, static_cast<void*>(&depth));
+        const_data[1] = depth_tensor;
+    } else if (memory_deps.count(1) > 0) {
+        auto depth_mem = memory_deps.at(1);
+
+        cldnn::mem_lock<uint8_t, mem_lock_type::read> depth_lock(depth_mem, impl_param.get_stream());
+        auto depth_ptr = depth_lock.data();
+
+        // update depth_tensor if depth value comes from memory_deps instead of Constant node
+        auto depth_tensor = make_tensor(depth_mem->get_layout(), depth_ptr);
+        const_data[1] = depth_tensor;
+    }
 
-    auto depth_tensor = ov::Tensor(ov::element::i64, ov::Shape{1}, static_cast<void*>(&depth));
-    std::unordered_map<size_t, ov::Tensor> const_data = {
-        {1, depth_tensor}
-    };
     std::vector<ShapeType> output_shapes =
         ov::op::v1::shape_infer(&op, input_shapes, ov::make_tensor_accessor(const_data));
     return {{output_shapes[0], dt, format::get_default_format(output_shapes[0].size())}};
diff --git a/src/plugins/intel_gpu/src/graph/program.cpp b/src/plugins/intel_gpu/src/graph/program.cpp
index 7a66d32795c17c..2bfaac84134387 100644
--- a/src/plugins/intel_gpu/src/graph/program.cpp
+++ b/src/plugins/intel_gpu/src/graph/program.cpp
@@ -436,7 +436,7 @@ void program::prepare_nodes(topology const& topology) {
     }
 }
 
-// add node's dependecies from its primitive dependencies
+// add node's dependencies from its primitive dependencies
 void program::add_node_dependencies(program_node* node) {
     auto deps = node->get_primitive()->dependencies();
     // add pointers to node's dependencies
@@ -453,7 +453,7 @@ void program::add_node_dependencies(program_node* node) {
 }
 
 /* helper method for program constructor from list of nodes which
-   copies src_node dependecies to the destination node dest_node dependencies.
+   copies src_node dependencies to the destination node dest_node dependencies.
    But only to those which appaer in this program implementation nodes_map */
 void program::copy_node_dependencies(program_node* dest_node, program_node* src_node) {
     if (dest_node->get_primitive()->id != src_node->get_primitive()->id) {
diff --git a/src/plugins/intel_gpu/src/graph/program_helpers.cpp b/src/plugins/intel_gpu/src/graph/program_helpers.cpp
index 256ba493311b7c..51e5d8510739e2 100644
--- a/src/plugins/intel_gpu/src/graph/program_helpers.cpp
+++ b/src/plugins/intel_gpu/src/graph/program_helpers.cpp
@@ -117,7 +117,8 @@ add_fusing_type onednn_add_fusing_helpers::get_add_fusing_type(
             && p_layout.data_padding == d_layout.data_padding
             && dep_node.get_users().size() == 1
             && !dep_node.is_constant()
-            && !p_node.is_type<pooling>()) {
+            && !p_node.is_type<pooling>()
+            && !(dep_node.get_program().is_body_program() && dep_node.is_type<input_layout>())) {
             return add_fusing_type::sum;
         } else if (p_layout.get_tensor() == d_layout.get_tensor()) {
             return add_fusing_type::binary_per_tensor;
diff --git a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/dynamic_quantize_gpu_kv_cache.cl b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/dynamic_quantize_gpu_kv_cache.cl
index 22a2f03c94564a..b0e363169e9e4d 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/dynamic_quantize_gpu_kv_cache.cl
+++ b/src/plugins/intel_gpu/src/kernel_selector/cl_kernels/dynamic_quantize_gpu_kv_cache.cl
@@ -83,11 +83,11 @@ KERNEL(dynamic_quantize_gpu_kv_cache)(
 #if ASYMMETRIC_QUANTIZATION
     min_value = work_group_reduce_min(min_value);
     max_value = work_group_reduce_max(max_value);
-    OUTPUT1_TYPE scale = (OUTPUT1_TYPE)((CHAR_MAX - CHAR_MIN) / (max_value - min_value));
-    OUTPUT1_TYPE zp = (OUTPUT1_TYPE)(-min_value * scale) - CHAR_MAX;
+    ACCUMULATOR_TYPE scale = (ACCUMULATOR_TYPE)((CHAR_MAX - CHAR_MIN) / (max_value - min_value));
+    ACCUMULATOR_TYPE zp = (ACCUMULATOR_TYPE)(-min_value * scale) - CHAR_MAX;
 #else
     max_value = work_group_reduce_max(max_value);
-    OUTPUT1_TYPE scale = 127.0h / max_value;
+    ACCUMULATOR_TYPE scale = 127.0h / max_value;
 #endif
 
 #ifdef APPEND_MODE
diff --git a/src/plugins/intel_gpu/src/kernel_selector/kernels/dynamic_quantize/dynamic_quantize_kernel_opt_kv_cache.cpp b/src/plugins/intel_gpu/src/kernel_selector/kernels/dynamic_quantize/dynamic_quantize_kernel_opt_kv_cache.cpp
index d0c99484e3f52e..8f7537eeeb5d7d 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/kernels/dynamic_quantize/dynamic_quantize_kernel_opt_kv_cache.cpp
+++ b/src/plugins/intel_gpu/src/kernel_selector/kernels/dynamic_quantize/dynamic_quantize_kernel_opt_kv_cache.cpp
@@ -141,6 +141,9 @@ JitConstants DynamicQuantizeKernelKVCache::GetJitConstants(const dynamic_quantiz
     jit.AddConstant(MakeJitConstant("ASYMMETRIC_QUANTIZATION", params.use_asymmetric_quantization));
     jit.AddConstant(MakeJitConstant("GROUP_SCALES_WITH_ZP", params.combine_scales_and_zp));
 
+    // Use FP32 accumulator type for scale/zp calculation
+    jit.Merge(MakeTypeJitConstants(Datatype::F32, "ACCUMULATOR"));
+
     bool rearrange_scales_order = false;
     const auto& scales_output_order = params.scales_output_order;
     if (!scales_output_order.empty()) {
diff --git a/src/plugins/intel_gpu/src/kernel_selector/kernels/permute/permute_kernel_f_y_axes.cpp b/src/plugins/intel_gpu/src/kernel_selector/kernels/permute/permute_kernel_f_y_axes.cpp
index 69756b02e2d9ff..deb25d17618347 100644
--- a/src/plugins/intel_gpu/src/kernel_selector/kernels/permute/permute_kernel_f_y_axes.cpp
+++ b/src/plugins/intel_gpu/src/kernel_selector/kernels/permute/permute_kernel_f_y_axes.cpp
@@ -214,6 +214,8 @@ bool PermuteKernel_f_y_axes::Validate(const Params& p) const {
     const auto& params = dynamic_cast<const permute_params&>(p);
     const auto& in = params.inputs[0];
     const auto in_layout = in.GetLayout();
+    const auto& out = params.outputs[0];
+    const auto& out_layout = out.GetLayout();
 
     const auto feature_div = GetDivisor(in.Feature().v);
     const auto y_div = GetDivisor(in.Y().v);
@@ -227,6 +229,10 @@ bool PermuteKernel_f_y_axes::Validate(const Params& p) const {
         return false;
     }
 
+    if (in_layout != out_layout) {
+        return false;
+    }
+
     // Accept only supported blocked layouts and SIMD sizes.
     if (!SimpleLayout(in_layout)) {
         const auto feature_block_size = GetFeatureBlockSize(params);
diff --git a/src/plugins/intel_gpu/src/plugin/ops/one_hot.cpp b/src/plugins/intel_gpu/src/plugin/ops/one_hot.cpp
index 9a7f8697d0b736..09e9d81db088df 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/one_hot.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/one_hot.cpp
@@ -7,7 +7,6 @@
 #include "transformations/utils/utils.hpp"
 
 #include "openvino/op/one_hot.hpp"
-
 #include "intel_gpu/primitives/one_hot.hpp"
 
 namespace ov {
@@ -49,21 +48,33 @@ static void CreateOneHotOp(ProgramBuilder& p, const std::shared_ptr<ov::op::v1::
         }
     }
 
-    int64_t depth = depth_value_node->cast_vector<int64_t>()[0];
-
     auto out_pshape = op->get_output_partial_shape(0);
     cldnn::tensor out_tensor = out_pshape.is_static() ? tensor_from_dims(out_pshape.to_shape()) : cldnn::tensor{};
 
-    auto oneHotPrim = cldnn::one_hot(layerName,
-                                     inputs[0],
-                                     out_tensor,
-                                     cldnn::element_type_to_data_type(op->get_output_element_type(0)),
-                                     axis,
-                                     depth,
-                                     on_value,
-                                     off_value);
-
-    p.add_primitive(*op, oneHotPrim);
+    if (depth_value_node) {
+        int64_t depth = depth_value_node->cast_vector<int64_t>()[0];
+        auto oneHotPrim = cldnn::one_hot(layerName,
+                                         inputs[0],
+                                         out_tensor,
+                                         cldnn::element_type_to_data_type(op->get_output_element_type(0)),
+                                         axis,
+                                         depth,
+                                         on_value,
+                                         off_value);
+
+        p.add_primitive(*op, oneHotPrim);
+    } else {
+        auto oneHotPrim = cldnn::one_hot(layerName,
+                                         inputs[0],
+                                         inputs[1],
+                                         out_tensor,
+                                         cldnn::element_type_to_data_type(op->get_output_element_type(0)),
+                                         axis,
+                                         on_value,
+                                         off_value);
+
+        p.add_primitive(*op, oneHotPrim);
+    }
 }
 
 REGISTER_FACTORY_IMPL(v1, OneHot);
diff --git a/src/plugins/intel_gpu/src/runtime/execution_config.cpp b/src/plugins/intel_gpu/src/runtime/execution_config.cpp
index 7c8e55cddfe593..44758f73289edb 100644
--- a/src/plugins/intel_gpu/src/runtime/execution_config.cpp
+++ b/src/plugins/intel_gpu/src/runtime/execution_config.cpp
@@ -246,6 +246,11 @@ void ExecutionConfig::apply_user_properties(const cldnn::device_info& info) {
         set_property(ov::intel_gpu::queue_type(QueueTypes::in_order));
     }
 
+    // Enable KV-cache compression by default for non-systolic platforms
+    if (!is_set_by_user(ov::hint::kv_cache_precision) && !info.supports_immad) {
+        set_property(ov::hint::kv_cache_precision(ov::element::i8));
+    }
+
     user_properties.clear();
 }
 
diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/kv_cache_sdpa.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/kv_cache_sdpa.cpp
index 16db9d89c28b4d..2563fe535a93d9 100644
--- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/kv_cache_sdpa.cpp
+++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/kv_cache_sdpa.cpp
@@ -47,8 +47,11 @@ class SDPAWithKVCacheTest : public ::testing::Test, public ::testing::WithParamI
         ov::AnyMap properties = {ov::hint::inference_precision(ov::element::f16),
                                  ov::intel_gpu::hint::enable_sdpa_optimization(true)};
 
-        if (p.compressed)
+        if (p.compressed) {
             properties.emplace(ov::hint::kv_cache_precision(ov::element::i8));
+        } else {
+            properties.emplace(ov::hint::kv_cache_precision(ov::element::undefined));
+        }
 
         const size_t n_heads = 16;
         const size_t n_features = 64;
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/dynamic_quantize_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/dynamic_quantize_gpu_test.cpp
index 5a78360eb1f6d8..c0e317ff6ce915 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/dynamic_quantize_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/dynamic_quantize_gpu_test.cpp
@@ -121,11 +121,10 @@ class dynamic_quantization_gpu_tests: public ::testing::Test {
         auto outputs = network->execute();
 
         auto output_mem = outputs.begin()->second.get_memory();
-        cldnn::mem_lock<uint8_t> output_ptr (output_mem, get_test_stream());
+        cldnn::mem_lock<ov::float16> output_ptr (output_mem, get_test_stream());
 
         auto ref_output_mem = get_ref_results();
-        cldnn::mem_lock<uint8_t> output_ptr_ref (ref_output_mem, get_test_stream());
-
+        cldnn::mem_lock<ov::float16> output_ptr_ref (ref_output_mem, get_test_stream());
         size_t count = 0;
         float max_diff = 0.f;
         float avg = 0.f;
@@ -135,7 +134,7 @@ class dynamic_quantization_gpu_tests: public ::testing::Test {
                 max_diff = abs_diff;
             avg += abs_diff;
             count++;
-            OPENVINO_ASSERT(abs_diff < 1);
+            ASSERT_LE(abs_diff, 1);
         }
         GPU_DEBUG_LOG << "---> count: " << count << ", max_diff:" << max_diff << ", avg_diff: " << (avg/count) << std::endl;
     }
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/permute_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/permute_gpu_test.cpp
index 9688ebe227071f..db9777a3a613d9 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/permute_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/permute_gpu_test.cpp
@@ -2175,6 +2175,76 @@ TEST(permute_gpu_f32_dynamic, bfyx_0_2_3_1) {
     }
 }
 
+TEST(permute_f_y_axes_fallback, b_fs_yx_fsv16) {
+    constexpr size_t array_size = 128;
+
+    auto& engine = get_test_engine();
+    if (!engine.get_device_info().supports_immad)
+        return;
+
+    auto input_layout_static = layout{ov::PartialShape{1, 8, 16, 1}, data_types::f32, format::bfyx};
+    auto input = engine.allocate_memory(input_layout_static);
+
+    std::vector<float> input_data;
+    input_data.reserve(array_size);
+    for (size_t i = 0; i < array_size; ++i)
+        input_data.push_back(static_cast<float>(i));
+
+    auto weights = engine.allocate_memory({ data_types::f32, format::bfyx, { 8, 16, 1, 1 } });
+
+    std::vector<float> weights_data;
+    weights_data.reserve(array_size);
+    for (size_t i = 0; i < array_size; ++i)
+      weights_data.push_back(static_cast<float>(1.0));
+
+    set_values(weights, weights_data);
+    set_values(input, input_data);
+
+    auto impl_desc_onednn = ov::intel_gpu::ImplementationDesc{format::b_fs_yx_fsv16, "", impl_types::onednn};
+    auto impl_forcing_map = ov::intel_gpu::ImplForcingMap{{"conv", impl_desc_onednn}};
+
+    topology topology;
+    topology.add(input_layout("input", input_layout_static));
+    topology.add(permute("permute", input_info("input"), { 0, 2, 1, 3 }));
+    topology.add(data("weights", weights));
+    topology.add(convolution("conv", input_info("permute"), "weights", "", 1, {1,1}, {1,1}, {0,0}, {0,0}, false));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    config.set_property(ov::intel_gpu::force_implementations(impl_forcing_map));
+
+    network network(engine, topology, config);
+    network.set_input_data("input", input);
+    auto outputs = network.execute();
+    ASSERT_EQ(outputs.size(), size_t(1));
+    ASSERT_EQ(outputs.begin()->first, "conv");
+
+    auto output = outputs.begin()->second.get_memory();
+
+    float answers[] = {
+        120.f, 120.f, 120.f, 120.f, 120.f, 120.f, 120.f, 120.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        376.f, 376.f, 376.f, 376.f, 376.f, 376.f, 376.f, 376.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        632.f, 632.f, 632.f, 632.f, 632.f, 632.f, 632.f, 632.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        888.f, 888.f, 888.f, 888.f, 888.f, 888.f, 888.f, 888.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        1144.f, 1144.f, 1144.f, 1144.f, 1144.f, 1144.f, 1144.f, 1144.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        1400.f, 1400.f, 1400.f, 1400.f, 1400.f, 1400.f, 1400.f, 1400.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        1656.f, 1656.f, 1656.f, 1656.f, 1656.f, 1656.f, 1656.f, 1656.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+        1912.f, 1912.f, 1912.f, 1912.f, 1912.f, 1912.f, 1912.f, 1912.f,
+        0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
+    };
+
+    cldnn::mem_lock<float> output_ptr(output, get_test_stream());
+    for (size_t i = 0; i < array_size; i++) {
+        ASSERT_FLOAT_EQ(answers[i], output_ptr[i]);
+    }
+}
+
 class permute_bfzyx_to_bfyxz: public TiledPermuteTest {};
 
 INSTANTIATE_TEST_SUITE_P(, permute_bfzyx_to_bfyxz,
diff --git a/src/plugins/intel_npu/src/backend/include/zero_device.hpp b/src/plugins/intel_npu/src/backend/include/zero_device.hpp
index 50f0d28ed210cd..aca3e97582fb58 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_device.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_device.hpp
@@ -58,8 +58,6 @@ class ZeroDevice : public IDevice {
 private:
     const std::shared_ptr<ZeroInitStructsHolder> _initStructs;
 
-    ze_graph_dditable_ext_curr_t& _graph_ddi_table_ext;
-
     ze_device_properties_t device_properties = {};
 
     ze_pci_ext_properties_t pci_properties = {};
diff --git a/src/plugins/intel_npu/src/backend/include/zero_host_tensor.hpp b/src/plugins/intel_npu/src/backend/include/zero_host_tensor.hpp
index a214c8e2cb2b5d..eee2c36c4aa0ed 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_host_tensor.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_host_tensor.hpp
@@ -13,8 +13,8 @@ namespace intel_npu {
 
 class ZeroHostTensor : public ov::ITensor {
 public:
-    ZeroHostTensor(std::shared_ptr<ov::IRemoteContext> context,
-                   std::shared_ptr<ZeroInitStructsHolder> init_structs,
+    ZeroHostTensor(const std::shared_ptr<ov::IRemoteContext>& context,
+                   const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
                    const ov::element::Type element_type,
                    const ov::Shape& shape,
                    const Config& config);
diff --git a/src/plugins/intel_npu/src/backend/include/zero_infer_request.hpp b/src/plugins/intel_npu/src/backend/include/zero_infer_request.hpp
index 31248b582250da..3efbdab666d1ba 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_infer_request.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_infer_request.hpp
@@ -63,7 +63,7 @@ class ZeroInferRequest final : public SyncInferRequest {
      * @param index The index corresponding to the position of the tensor inside the I/O structures.
      * @param isInput Used for identifying the structures to which the tensor belongs.
      */
-    void set_tensor_data(const std::shared_ptr<ov::ITensor> tensor, const size_t index, const bool isInput);
+    void set_tensor_data(const std::shared_ptr<ov::ITensor>& tensor, const size_t index, const bool isInput);
 
     /**
      * @brief Check the received remote tensor and copy it to the Level Zero tensor
@@ -71,7 +71,9 @@ class ZeroInferRequest final : public SyncInferRequest {
      * @param index The index corresponding to the position of the tensor inside the I/O structures.
      * @param isInput Used for identifying the structures to which the tensor belongs.
      */
-    void set_remote_tensor_data(const std::shared_ptr<ZeroRemoteTensor> tensor, const size_t index, const bool isInput);
+    void set_remote_tensor_data(const std::shared_ptr<ZeroRemoteTensor>& tensor,
+                                const size_t index,
+                                const bool isInput);
 
     void check_network_precision(const ov::element::Type_t precision) const override;
     void create_pipeline();
diff --git a/src/plugins/intel_npu/src/backend/include/zero_pipeline.hpp b/src/plugins/intel_npu/src/backend/include/zero_pipeline.hpp
index 92a473a9fc412c..5b7f488d3eb96a 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_pipeline.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_pipeline.hpp
@@ -25,7 +25,7 @@ struct Pipeline {
              const std::shared_ptr<IGraph>& graph,
              zeroProfiling::ProfilingPool& profiling_pool,
              zeroProfiling::ProfilingQuery& profiling_query,
-             std::shared_ptr<zeroProfiling::NpuInferProfiling> npu_profiling,
+             const std::shared_ptr<zeroProfiling::NpuInferProfiling>& npu_profiling,
              const std::vector<std::vector<std::optional<TensorData>>>& inputTensorsData,
              const std::vector<std::optional<TensorData>>& outputTensorsData,
              size_t numberOfCommandLists,
diff --git a/src/plugins/intel_npu/src/backend/include/zero_profiling.hpp b/src/plugins/intel_npu/src/backend/include/zero_profiling.hpp
index 17e263a7aaf620..9b799f2b5ef3dd 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_profiling.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_profiling.hpp
@@ -10,8 +10,10 @@
 #include <climits>
 #include <map>
 
+#include "intel_npu/common/igraph.hpp"
 #include "intel_npu/config/compiler.hpp"
 #include "intel_npu/utils/logger/logger.hpp"
+#include "intel_npu/utils/zero/zero_init.hpp"
 #include "intel_npu/utils/zero/zero_types.hpp"
 #include "openvino/runtime/profiling_info.hpp"
 
@@ -23,31 +25,29 @@ using LayerStatistics = std::vector<ov::ProfilingInfo>;
 constexpr uint32_t POOL_SIZE = 1;
 
 struct ProfilingPool {
-    ProfilingPool(ze_graph_handle_t graph_handle,
-                  uint32_t profiling_count,
-                  ze_graph_profiling_dditable_ext_curr_t& graph_profiling_ddi_table_ext)
-        : _graph_handle(graph_handle),
-          _profiling_count(profiling_count),
-          _graph_profiling_ddi_table_ext(graph_profiling_ddi_table_ext) {}
+    ProfilingPool(const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
+                  const std::shared_ptr<IGraph>& graph,
+                  uint32_t profiling_count)
+        : _init_structs(init_structs),
+          _graph(graph),
+          _profiling_count(profiling_count) {}
     ProfilingPool(const ProfilingPool&) = delete;
     ProfilingPool& operator=(const ProfilingPool&) = delete;
     bool create();
 
     ~ProfilingPool();
 
-    ze_graph_handle_t _graph_handle;
+    std::shared_ptr<ZeroInitStructsHolder> _init_structs;
+    std::shared_ptr<IGraph> _graph;
     const uint32_t _profiling_count;
+
     ze_graph_profiling_pool_handle_t _handle = nullptr;
-    ze_graph_profiling_dditable_ext_curr_t& _graph_profiling_ddi_table_ext;
 };
 
 struct ProfilingQuery {
-    ProfilingQuery(uint32_t index,
-                   ze_device_handle_t device_handle,
-                   ze_graph_profiling_dditable_ext_curr_t& graph_profiling_ddi_table_ext)
-        : _index(index),
-          _device_handle(device_handle),
-          _graph_profiling_ddi_table_ext(graph_profiling_ddi_table_ext) {}
+    ProfilingQuery(const std::shared_ptr<ZeroInitStructsHolder>& init_structs, uint32_t index)
+        : _init_structs(init_structs),
+          _index(index) {}
     ProfilingQuery(const ProfilingQuery&) = delete;
     ProfilingQuery& operator=(const ProfilingQuery&) = delete;
     void create(const ze_graph_profiling_pool_handle_t& profiling_pool);
@@ -64,10 +64,10 @@ struct ProfilingQuery {
     void getProfilingProperties(ze_device_profiling_data_properties_t* properties) const;
     void verifyProfilingProperties() const;
 
+    std::shared_ptr<ZeroInitStructsHolder> _init_structs;
     const uint32_t _index;
-    ze_device_handle_t _device_handle;
+
     ze_graph_profiling_query_handle_t _handle = nullptr;
-    ze_graph_profiling_dditable_ext_curr_t& _graph_profiling_ddi_table_ext;
 };
 
 extern template std::vector<uint8_t> ProfilingQuery::getData<uint8_t>() const;
@@ -75,7 +75,7 @@ extern template std::vector<uint8_t> ProfilingQuery::getData<uint8_t>() const;
 using NpuInferStatistics = std::vector<ov::ProfilingInfo>;
 
 struct NpuInferProfiling final {
-    explicit NpuInferProfiling(ze_context_handle_t context, ze_device_handle_t device_handle, ov::log::Level loglevel);
+    explicit NpuInferProfiling(const std::shared_ptr<ZeroInitStructsHolder>& init_structs, ov::log::Level loglevel);
     NpuInferProfiling(const NpuInferProfiling&) = delete;
     NpuInferProfiling& operator=(const NpuInferProfiling&) = delete;
     NpuInferProfiling(NpuInferProfiling&&) = delete;
@@ -91,8 +91,7 @@ struct NpuInferProfiling final {
     void* npu_ts_infer_end = 0;
 
 private:
-    ze_context_handle_t _context = nullptr;
-    ze_device_handle_t _device_handle;
+    std::shared_ptr<ZeroInitStructsHolder> _init_structs;
     ov::log::Level _loglevel;
     Logger _logger;
     ze_device_properties_t _dev_properties = {};
diff --git a/src/plugins/intel_npu/src/backend/include/zero_remote_tensor.hpp b/src/plugins/intel_npu/src/backend/include/zero_remote_tensor.hpp
index 5b08643704b651..aabe5e9bb4e1bf 100644
--- a/src/plugins/intel_npu/src/backend/include/zero_remote_tensor.hpp
+++ b/src/plugins/intel_npu/src/backend/include/zero_remote_tensor.hpp
@@ -16,8 +16,8 @@ namespace intel_npu {
 
 class ZeroRemoteTensor : public RemoteTensor {
 public:
-    ZeroRemoteTensor(std::shared_ptr<ov::IRemoteContext> context,
-                     std::shared_ptr<ZeroInitStructsHolder> init_structs,
+    ZeroRemoteTensor(const std::shared_ptr<ov::IRemoteContext>& context,
+                     const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
                      const ov::element::Type& element_type,
                      const ov::Shape& shape,
                      const Config& config,
diff --git a/src/plugins/intel_npu/src/backend/src/zero_device.cpp b/src/plugins/intel_npu/src/backend/src/zero_device.cpp
index 6e16dde3b120bf..b982fd14ee0d95 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_device.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_device.cpp
@@ -15,7 +15,6 @@ using namespace intel_npu;
 
 ZeroDevice::ZeroDevice(const std::shared_ptr<ZeroInitStructsHolder>& initStructs)
     : _initStructs(initStructs),
-      _graph_ddi_table_ext(_initStructs->getGraphDdiTable()),
       log("ZeroDevice", Logger::global().level()) {
     log.debug("ZeroDevice::ZeroDevice init");
     device_properties.stype = ZE_STRUCTURE_TYPE_DEVICE_PROPERTIES;
@@ -121,9 +120,10 @@ uint32_t ZeroDevice::getMaxNumSlices() const {
 
 uint64_t ZeroDevice::getAllocMemSize() const {
     ze_graph_memory_query_t query{};
-    ze_result_t result =
-        _graph_ddi_table_ext.pfnQueryContextMemory(_initStructs->getContext(), ZE_GRAPH_QUERY_MEMORY_DDR, &query);
-    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnQueryContextMemory", result, _graph_ddi_table_ext);
+    ze_result_t result = _initStructs->getGraphDdiTable().pfnQueryContextMemory(_initStructs->getContext(),
+                                                                                ZE_GRAPH_QUERY_MEMORY_DDR,
+                                                                                &query);
+    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnQueryContextMemory", result, _initStructs->getGraphDdiTable());
 
     return query.allocated;
 }
@@ -132,9 +132,10 @@ uint64_t ZeroDevice::getTotalMemSize() const {
 #define LEGACY_MAX_MEM_ALLOC_SIZE_BYTES (2147483648)  // 2GB in base-2
 
     ze_graph_memory_query_t query{};
-    ze_result_t result =
-        _graph_ddi_table_ext.pfnQueryContextMemory(_initStructs->getContext(), ZE_GRAPH_QUERY_MEMORY_DDR, &query);
-    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnQueryContextMemory", result, _graph_ddi_table_ext);
+    ze_result_t result = _initStructs->getGraphDdiTable().pfnQueryContextMemory(_initStructs->getContext(),
+                                                                                ZE_GRAPH_QUERY_MEMORY_DDR,
+                                                                                &query);
+    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnQueryContextMemory", result, _initStructs->getGraphDdiTable());
 
     // For drivers with graph_extension < 1.9 we report fixed 2GB max allocation size (old drivers don't support more)
     // For drivers with graph_extension > 1.9 we report the value they return
diff --git a/src/plugins/intel_npu/src/backend/src/zero_host_tensor.cpp b/src/plugins/intel_npu/src/backend/src/zero_host_tensor.cpp
index e0f1094e67da05..71d9c5f4b3c20c 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_host_tensor.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_host_tensor.cpp
@@ -8,8 +8,8 @@
 
 namespace intel_npu {
 
-ZeroHostTensor::ZeroHostTensor(std::shared_ptr<ov::IRemoteContext> context,
-                               std::shared_ptr<ZeroInitStructsHolder> init_structs,
+ZeroHostTensor::ZeroHostTensor(const std::shared_ptr<ov::IRemoteContext>& context,
+                               const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
                                const ov::element::Type element_type,
                                const ov::Shape& shape,
                                const Config& config)
diff --git a/src/plugins/intel_npu/src/backend/src/zero_infer_request.cpp b/src/plugins/intel_npu/src/backend/src/zero_infer_request.cpp
index 1c5ceecfac1961..88dfaf944a8b34 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_infer_request.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_infer_request.cpp
@@ -167,10 +167,8 @@ ZeroInferRequest::ZeroInferRequest(const std::shared_ptr<ZeroInitStructsHolder>&
       _levelZeroOutputTensors(_metadata.outputs.size(), nullptr),
       _inputTensorsData(_metadata.inputs.size(), std::vector<std::optional<TensorData>>(1, std::nullopt)),
       _outputTensorsData(_metadata.outputs.size(), std::nullopt),
-      _profilingPool(static_cast<ze_graph_handle_t>(_graph->get_handle()),
-                     zeroProfiling::POOL_SIZE,
-                     _initStructs->getProfilingDdiTable()),
-      _profilingQuery(0, _initStructs->getDevice(), _initStructs->getProfilingDdiTable()) {
+      _profilingPool(_initStructs, _graph, zeroProfiling::POOL_SIZE),
+      _profilingQuery(_initStructs, 0) {
     _logger.debug("ZeroInferRequest::ZeroInferRequest - SyncInferRequest");
     const std::vector<ArgumentDescriptor>& executorInputDescriptors = _graph->get_input_descriptors();
     const std::vector<ArgumentDescriptor>& executorOutputDescriptors = _graph->get_output_descriptors();
@@ -178,9 +176,7 @@ ZeroInferRequest::ZeroInferRequest(const std::shared_ptr<ZeroInitStructsHolder>&
     auto proftype = config.get<PROFILING_TYPE>();
     if (proftype == ov::intel_npu::ProfilingType::INFER) {
         _logger.debug("ZeroInferRequest::ZeroInferRequest - profiling type == ov::intel_npu::ProfilingType::INFER");
-        _npuProfiling = std::make_shared<zeroProfiling::NpuInferProfiling>(_initStructs->getContext(),
-                                                                           _initStructs->getDevice(),
-                                                                           _config.get<LOG_LEVEL>());
+        _npuProfiling = std::make_shared<zeroProfiling::NpuInferProfiling>(_initStructs, _config.get<LOG_LEVEL>());
     }
 
     _properties.stype = ZE_STRUCTURE_TYPE_DEVICE_PROPERTIES;
@@ -296,7 +292,7 @@ void ZeroInferRequest::create_pipeline() {
     _logger.debug("ZeroInferRequest::create_pipeline - SyncInferRequest completed");
 }
 
-void ZeroInferRequest::set_tensor_data(const std::shared_ptr<ov::ITensor> tensor,
+void ZeroInferRequest::set_tensor_data(const std::shared_ptr<ov::ITensor>& tensor,
                                        const size_t index,
                                        const bool isInput) {
     OV_ITT_TASK_CHAIN(ZERO_SET_TENSOR, itt::domains::LevelZeroBackend, "set_tensor", "set_tensor_data");
@@ -347,7 +343,7 @@ void ZeroInferRequest::set_tensor_data(const std::shared_ptr<ov::ITensor> tensor
     }
 }
 
-void ZeroInferRequest::set_remote_tensor_data(const std::shared_ptr<ZeroRemoteTensor> tensor,
+void ZeroInferRequest::set_remote_tensor_data(const std::shared_ptr<ZeroRemoteTensor>& tensor,
                                               const size_t index,
                                               const bool isInput) {
     OV_ITT_TASK_CHAIN(ZERO_SET_REMOTE_TENSOR, itt::domains::LevelZeroBackend, "set_tensor", "set_remote_tensor_data");
diff --git a/src/plugins/intel_npu/src/backend/src/zero_pipeline.cpp b/src/plugins/intel_npu/src/backend/src/zero_pipeline.cpp
index 34eb71eaf112f7..c782c3e0684f0d 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_pipeline.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_pipeline.cpp
@@ -20,7 +20,7 @@ Pipeline::Pipeline(const Config& config,
                    const std::shared_ptr<IGraph>& graph,
                    zeroProfiling::ProfilingPool& profiling_pool,
                    zeroProfiling::ProfilingQuery& profiling_query,
-                   std::shared_ptr<zeroProfiling::NpuInferProfiling> npu_profiling,
+                   const std::shared_ptr<zeroProfiling::NpuInferProfiling>& npu_profiling,
                    const std::vector<std::vector<std::optional<TensorData>>>& inputTensorsData,
                    const std::vector<std::optional<TensorData>>& outputTensorsData,
                    size_t numberOfCommandLists,
@@ -30,7 +30,7 @@ Pipeline::Pipeline(const Config& config,
       _event_pool{initStructs->getDevice(),
                   initStructs->getContext(),
                   numberOfCommandLists ? static_cast<uint32_t>(numberOfCommandLists) : 1},
-      _npu_profiling(std::move(npu_profiling)),
+      _npu_profiling(npu_profiling),
       _logger("Pipeline", _config.get<LOG_LEVEL>()) {
     OV_ITT_SCOPED_TASK(itt::domains::LevelZeroBackend, "Zero_infer_request::Pipeline::Pipeline");
     _logger.debug("Pipeline - initialize started");
@@ -45,9 +45,7 @@ Pipeline::Pipeline(const Config& config,
     _logger.debug("Pipeline - emplace_back _event_pool and _command_queue");
     for (size_t i = 0; i < numberOfCommandLists; i++) {
         _command_lists.emplace_back(
-            std::make_unique<CommandList>(initStructs->getDevice(),
-                                          initStructs->getContext(),
-                                          initStructs->getGraphDdiTable(),
+            std::make_unique<CommandList>(initStructs,
                                           group_ordinal,
                                           initStructs->getMutableCommandListVersion() ? true : false));
         _events.emplace_back(std::make_unique<Event>(_event_pool.handle(), static_cast<uint32_t>(i)));
diff --git a/src/plugins/intel_npu/src/backend/src/zero_profiling.cpp b/src/plugins/intel_npu/src/backend/src/zero_profiling.cpp
index 52302b38df512d..f85c2c5f713b74 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_profiling.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_profiling.cpp
@@ -35,20 +35,21 @@ struct ZeProfilingTypeId<uint8_t> {
 };
 
 bool ProfilingPool::create() {
-    auto ret = _graph_profiling_ddi_table_ext.pfnProfilingPoolCreate(_graph_handle, _profiling_count, &_handle);
+    auto ret =
+        _init_structs->getProfilingDdiTable().pfnProfilingPoolCreate(_graph->get_handle(), _profiling_count, &_handle);
     return ((ZE_RESULT_SUCCESS == ret) && (_handle != nullptr));
 }
 
 ProfilingPool::~ProfilingPool() {
     if (_handle) {
-        _graph_profiling_ddi_table_ext.pfnProfilingPoolDestroy(_handle);
+        _init_structs->getProfilingDdiTable().pfnProfilingPoolDestroy(_handle);
     }
 }
 
 void ProfilingQuery::create(const ze_graph_profiling_pool_handle_t& profiling_pool) {
     THROW_ON_FAIL_FOR_LEVELZERO(
         "pfnProfilingQueryCreate",
-        _graph_profiling_ddi_table_ext.pfnProfilingQueryCreate(profiling_pool, _index, &_handle));
+        _init_structs->getProfilingDdiTable().pfnProfilingQueryCreate(profiling_pool, _index, &_handle));
 }
 
 LayerStatistics ProfilingQuery::getLayerStatistics() const {
@@ -59,7 +60,7 @@ LayerStatistics ProfilingQuery::getLayerStatistics() const {
 
 ProfilingQuery::~ProfilingQuery() {
     if (_handle) {
-        _graph_profiling_ddi_table_ext.pfnProfilingQueryDestroy(_handle);
+        _init_structs->getProfilingDdiTable().pfnProfilingQueryDestroy(_handle);
     }
 }
 
@@ -69,7 +70,7 @@ void ProfilingQuery::queryGetData(const ze_graph_profiling_type_t profilingType,
     if (_handle && pSize) {
         THROW_ON_FAIL_FOR_LEVELZERO(
             "pfnProfilingQueryGetData",
-            _graph_profiling_ddi_table_ext.pfnProfilingQueryGetData(_handle, profilingType, pSize, pData));
+            _init_structs->getProfilingDdiTable().pfnProfilingQueryGetData(_handle, profilingType, pSize, pData));
     }
 }
 
@@ -95,7 +96,8 @@ void ProfilingQuery::getProfilingProperties(ze_device_profiling_data_properties_
     if (_handle && properties) {
         THROW_ON_FAIL_FOR_LEVELZERO(
             "getProfilingProperties",
-            _graph_profiling_ddi_table_ext.pfnDeviceGetProfilingDataProperties(_device_handle, properties));
+            _init_structs->getProfilingDdiTable().pfnDeviceGetProfilingDataProperties(_init_structs->getDevice(),
+                                                                                      properties));
     }
 }
 
@@ -179,30 +181,29 @@ NpuInferStatistics NpuInferProfiling::getNpuInferStatistics() const {
     return npuPerfCounts;
 }
 
-NpuInferProfiling::NpuInferProfiling(ze_context_handle_t context,
-                                     ze_device_handle_t device_handle,
+NpuInferProfiling::NpuInferProfiling(const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
                                      ov::log::Level loglevel)
-    : _context(context),
-      _device_handle(device_handle),
+    : _init_structs(init_structs),
       _loglevel(loglevel),
       _logger("InferProfiling", loglevel) {
     /// Fetch and store the device timer resolution
     _dev_properties.stype = ZE_STRUCTURE_TYPE_DEVICE_PROPERTIES_1_2;
-    THROW_ON_FAIL_FOR_LEVELZERO("zeDeviceGetProperties", zeDeviceGetProperties(_device_handle, &_dev_properties));
+    THROW_ON_FAIL_FOR_LEVELZERO("zeDeviceGetProperties",
+                                zeDeviceGetProperties(_init_structs->getDevice(), &_dev_properties));
     /// Request mem allocations
     ze_host_mem_alloc_desc_t desc = {ZE_STRUCTURE_TYPE_HOST_MEM_ALLOC_DESC,
                                      nullptr,
                                      ZE_HOST_MEM_ALLOC_FLAG_BIAS_CACHED};
     THROW_ON_FAIL_FOR_LEVELZERO(
         "zeMemAllocHost",
-        zeMemAllocHost(_context,
+        zeMemAllocHost(_init_structs->getContext(),
                        &desc,
                        sizeof(uint64_t),
                        64,
                        &npu_ts_infer_start));  // align to 64 bytes to match npu l2 cache line size
     THROW_ON_FAIL_FOR_LEVELZERO(
         "zeMemAllocHost",
-        zeMemAllocHost(_context,
+        zeMemAllocHost(_init_structs->getContext(),
                        &desc,
                        sizeof(uint64_t),
                        64,
@@ -235,13 +236,13 @@ int64_t NpuInferProfiling::convertCCtoUS(int64_t val_cc) const {
 NpuInferProfiling::~NpuInferProfiling() {
     /// deallocate npu_ts_infer_start and npu_ts_infer_end, allocated externally by ze driver
     if (npu_ts_infer_start != nullptr) {
-        auto ze_ret = zeMemFree(_context, npu_ts_infer_start);
+        auto ze_ret = zeMemFree(_init_structs->getContext(), npu_ts_infer_start);
         if (ZE_RESULT_SUCCESS != ze_ret) {
             _logger.error("zeMemFree on npu_ts_infer_start failed %#X", uint64_t(ze_ret));
         }
     }
     if (npu_ts_infer_end != nullptr) {
-        auto ze_ret = zeMemFree(_context, npu_ts_infer_end);
+        auto ze_ret = zeMemFree(_init_structs->getContext(), npu_ts_infer_end);
         if (ZE_RESULT_SUCCESS != ze_ret) {
             _logger.error("zeMemFree on npu_ts_infer_end failed %#X", uint64_t(ze_ret));
         }
diff --git a/src/plugins/intel_npu/src/backend/src/zero_remote_tensor.cpp b/src/plugins/intel_npu/src/backend/src/zero_remote_tensor.cpp
index 8419fec7a8612f..bb046b50f99cbd 100644
--- a/src/plugins/intel_npu/src/backend/src/zero_remote_tensor.cpp
+++ b/src/plugins/intel_npu/src/backend/src/zero_remote_tensor.cpp
@@ -21,18 +21,18 @@ constexpr std::size_t STANDARD_PAGE_SIZE = 4096;
 
 namespace intel_npu {
 
-ZeroRemoteTensor::ZeroRemoteTensor(std::shared_ptr<ov::IRemoteContext> context,
-                                   std::shared_ptr<ZeroInitStructsHolder> init_structs,
+ZeroRemoteTensor::ZeroRemoteTensor(const std::shared_ptr<ov::IRemoteContext>& context,
+                                   const std::shared_ptr<ZeroInitStructsHolder>& init_structs,
                                    const ov::element::Type& element_type,
                                    const ov::Shape& shape,
                                    const Config& config,
                                    TensorType tensor_type,
                                    MemType mem_type,
                                    void* mem)
-    : RemoteTensor(std::move(context), element_type, shape),
+    : RemoteTensor(context, element_type, shape),
       _config(config),
       _logger("ZeroRemoteContext", _config.get<LOG_LEVEL>()),
-      _init_structs(std::move(init_structs)),
+      _init_structs(init_structs),
       _tensor_type(tensor_type),
       _mem_type(mem_type),
       _mem(mem) {
diff --git a/src/plugins/intel_npu/src/common/include/intel_npu/common/remote_tensor.hpp b/src/plugins/intel_npu/src/common/include/intel_npu/common/remote_tensor.hpp
index d485052c989183..8a6edeb2e8d4ed 100644
--- a/src/plugins/intel_npu/src/common/include/intel_npu/common/remote_tensor.hpp
+++ b/src/plugins/intel_npu/src/common/include/intel_npu/common/remote_tensor.hpp
@@ -20,7 +20,7 @@ namespace intel_npu {
  */
 class RemoteTensor : public ov::IRemoteTensor {
 public:
-    RemoteTensor(std::shared_ptr<ov::IRemoteContext> context,
+    RemoteTensor(const std::shared_ptr<ov::IRemoteContext>& context,
                  const ov::element::Type& element_type,
                  const ov::Shape& shape);
 
diff --git a/src/plugins/intel_npu/src/common/src/remote_tensor.cpp b/src/plugins/intel_npu/src/common/src/remote_tensor.cpp
index 2d81de4aae65bf..a12ac7dca81710 100644
--- a/src/plugins/intel_npu/src/common/src/remote_tensor.cpp
+++ b/src/plugins/intel_npu/src/common/src/remote_tensor.cpp
@@ -10,10 +10,10 @@
 
 namespace intel_npu {
 
-RemoteTensor::RemoteTensor(std::shared_ptr<ov::IRemoteContext> context,
+RemoteTensor::RemoteTensor(const std::shared_ptr<ov::IRemoteContext>& context,
                            const ov::element::Type& element_type,
                            const ov::Shape& shape)
-    : _context(std::move(context)),
+    : _context(context),
       _element_type(element_type),
       _shape(shape),
       _capacity(shape) {
diff --git a/src/plugins/intel_npu/src/compiler_adapter/src/driver_graph.cpp b/src/plugins/intel_npu/src/compiler_adapter/src/driver_graph.cpp
index e5db5c561f7c1d..84759bf802f1c1 100644
--- a/src/plugins/intel_npu/src/compiler_adapter/src/driver_graph.cpp
+++ b/src/plugins/intel_npu/src/compiler_adapter/src/driver_graph.cpp
@@ -109,12 +109,10 @@ void DriverGraph::initialize(const Config& config) {
         turbo = config.get<TURBO>();
     }
 
-    _command_queue = std::make_shared<CommandQueue>(_zeroInitStruct->getDevice(),
-                                                    _zeroInitStruct->getContext(),
+    _command_queue = std::make_shared<CommandQueue>(_zeroInitStruct,
                                                     zeroUtils::toZeQueuePriority(config.get<MODEL_PRIORITY>()),
-                                                    _zeroInitStruct->getCommandQueueDdiTable(),
-                                                    turbo,
-                                                    groupOrdinal);
+                                                    groupOrdinal,
+                                                    turbo);
 
     if (config.has<WORKLOAD_TYPE>()) {
         set_workload_type(config.get<WORKLOAD_TYPE>());
diff --git a/src/plugins/intel_npu/src/compiler_adapter/src/plugin_graph.cpp b/src/plugins/intel_npu/src/compiler_adapter/src/plugin_graph.cpp
index cb57844b709ff7..8f60efd50af75c 100644
--- a/src/plugins/intel_npu/src/compiler_adapter/src/plugin_graph.cpp
+++ b/src/plugins/intel_npu/src/compiler_adapter/src/plugin_graph.cpp
@@ -104,12 +104,10 @@ void PluginGraph::initialize(const Config& config) {
         turbo = config.get<TURBO>();
     }
 
-    _command_queue = std::make_shared<CommandQueue>(_zeroInitStruct->getDevice(),
-                                                    _zeroInitStruct->getContext(),
+    _command_queue = std::make_shared<CommandQueue>(_zeroInitStruct,
                                                     zeroUtils::toZeQueuePriority(config.get<MODEL_PRIORITY>()),
-                                                    _zeroInitStruct->getCommandQueueDdiTable(),
-                                                    turbo,
-                                                    groupOrdinal);
+                                                    groupOrdinal,
+                                                    turbo);
 
     if (config.has<WORKLOAD_TYPE>()) {
         set_workload_type(config.get<WORKLOAD_TYPE>());
diff --git a/src/plugins/intel_npu/src/compiler_adapter/src/ze_graph_ext_wrappers.cpp b/src/plugins/intel_npu/src/compiler_adapter/src/ze_graph_ext_wrappers.cpp
index 095f470e15e02f..fad389ca30e0c7 100644
--- a/src/plugins/intel_npu/src/compiler_adapter/src/ze_graph_ext_wrappers.cpp
+++ b/src/plugins/intel_npu/src/compiler_adapter/src/ze_graph_ext_wrappers.cpp
@@ -173,17 +173,9 @@ void ZeGraphExtWrappers<TableExtension>::initialize_graph_through_command_list(z
     auto groupOrdinal = zeroUtils::findGroupOrdinal(_zeroInitStruct->getDevice(), deviceProperties);
 
     _logger.debug("ZeGraphExtWrappers::initialize_graph_through_command_list init start - create graph_command_list");
-    CommandList graph_command_list(_zeroInitStruct->getDevice(),
-                                   _zeroInitStruct->getContext(),
-                                   _zeroInitStruct->getGraphDdiTable(),
-                                   groupOrdinal);
+    CommandList graph_command_list(_zeroInitStruct, groupOrdinal);
     _logger.debug("ZeGraphExtWrappers::initialize_graph_through_command_list - create graph_command_queue");
-    CommandQueue graph_command_queue(_zeroInitStruct->getDevice(),
-                                     _zeroInitStruct->getContext(),
-                                     ZE_COMMAND_QUEUE_PRIORITY_NORMAL,
-                                     _zeroInitStruct->getCommandQueueDdiTable(),
-                                     false,
-                                     groupOrdinal);
+    CommandQueue graph_command_queue(_zeroInitStruct, ZE_COMMAND_QUEUE_PRIORITY_NORMAL, groupOrdinal, false);
     _logger.debug("ZeGraphExtWrappers::initialize_graph_through_command_list - create fence");
     Fence fence(graph_command_queue);
 
diff --git a/src/plugins/intel_npu/src/plugin/include/remote_context.hpp b/src/plugins/intel_npu/src/plugin/include/remote_context.hpp
index b6b8df5915382f..e0a9bb0d3f3893 100644
--- a/src/plugins/intel_npu/src/plugin/include/remote_context.hpp
+++ b/src/plugins/intel_npu/src/plugin/include/remote_context.hpp
@@ -16,7 +16,7 @@ namespace intel_npu {
 
 class RemoteContextImpl : public ov::IRemoteContext {
 public:
-    RemoteContextImpl(std::shared_ptr<const NPUBackends> backends, const Config& config);
+    RemoteContextImpl(const std::shared_ptr<const NPUBackends>& backends, const Config& config);
 
     /**
      * @brief Returns name of a device on which underlying object is allocated.
diff --git a/src/plugins/intel_npu/src/plugin/src/remote_context.cpp b/src/plugins/intel_npu/src/plugin/src/remote_context.cpp
index 938057668a7df0..a5f2cfb0e53c92 100644
--- a/src/plugins/intel_npu/src/plugin/src/remote_context.cpp
+++ b/src/plugins/intel_npu/src/plugin/src/remote_context.cpp
@@ -29,7 +29,7 @@ std::optional<Type> extract_object(const ov::AnyMap& params, const ov::Property<
 
 namespace intel_npu {
 
-RemoteContextImpl::RemoteContextImpl(std::shared_ptr<const NPUBackends> backends, const Config& config)
+RemoteContextImpl::RemoteContextImpl(const std::shared_ptr<const NPUBackends>& backends, const Config& config)
     : _backends(backends),
       _config(config),
       _properties({l0_context(backends->getContext())}),
diff --git a/src/plugins/intel_npu/src/utils/include/intel_npu/utils/zero/zero_wrappers.hpp b/src/plugins/intel_npu/src/utils/include/intel_npu/utils/zero/zero_wrappers.hpp
index afd6813a66206e..9b5b1b4540fbe7 100644
--- a/src/plugins/intel_npu/src/utils/include/intel_npu/utils/zero/zero_wrappers.hpp
+++ b/src/plugins/intel_npu/src/utils/include/intel_npu/utils/zero/zero_wrappers.hpp
@@ -7,6 +7,7 @@
 #include <ze_api.h>
 
 #include "intel_npu/utils/logger/logger.hpp"
+#include "intel_npu/utils/zero/zero_init.hpp"
 #include "intel_npu/utils/zero/zero_types.hpp"
 #include "intel_npu/utils/zero/zero_utils.hpp"
 
@@ -59,9 +60,7 @@ class CommandList {
 public:
     friend class CommandQueue;
     CommandList() = delete;
-    CommandList(const ze_device_handle_t& device_handle,
-                const ze_context_handle_t& context,
-                ze_graph_dditable_ext_curr_t& graph_ddi_table_ext,
+    CommandList(const std::shared_ptr<ZeroInitStructsHolder>& initStructs,
                 const uint32_t& group_ordinal,
                 bool mtci_is_supported = false);
     CommandList(const CommandList&) = delete;
@@ -85,12 +84,12 @@ class CommandList {
     }
 
 private:
-    ze_command_list_handle_t _handle = nullptr;
-    const ze_context_handle_t _context = nullptr;
-    ze_graph_dditable_ext_curr_t& _graph_ddi_table_ext;
-    uint64_t _command_id = 0;
+    std::shared_ptr<ZeroInitStructsHolder> _initStructs;
 
     Logger _log;
+
+    uint64_t _command_id = 0;
+    ze_command_list_handle_t _handle = nullptr;
 };
 
 class Fence {
@@ -118,12 +117,10 @@ class Fence {
 class CommandQueue {
 public:
     CommandQueue() = delete;
-    CommandQueue(const ze_device_handle_t& device_handle,
-                 const ze_context_handle_t& context,
+    CommandQueue(const std::shared_ptr<ZeroInitStructsHolder>& initStructs,
                  const ze_command_queue_priority_t& priority,
-                 ze_command_queue_npu_dditable_ext_curr_t& command_queue_npu_dditable_ext,
-                 bool turbo,
-                 const uint32_t& group_ordinal);
+                 const uint32_t& group_ordinal,
+                 bool turbo = false);
     CommandQueue(const CommandQueue&) = delete;
     CommandQueue(CommandQueue&&) = delete;
     CommandQueue& operator=(const CommandQueue&) = delete;
@@ -138,11 +135,11 @@ class CommandQueue {
     }
 
 private:
-    ze_command_queue_handle_t _handle = nullptr;
-    ze_context_handle_t _context = nullptr;
-    ze_command_queue_npu_dditable_ext_curr_t& _command_queue_npu_dditable_ext;
+    std::shared_ptr<ZeroInitStructsHolder> _initStructs;
 
     Logger _log;
+
+    ze_command_queue_handle_t _handle = nullptr;
 };
 
 }  // namespace intel_npu
diff --git a/src/plugins/intel_npu/src/utils/src/zero/zero_wrappers.cpp b/src/plugins/intel_npu/src/utils/src/zero/zero_wrappers.cpp
index 32a497552fc146..39bd92e7ecffd0 100644
--- a/src/plugins/intel_npu/src/utils/src/zero/zero_wrappers.cpp
+++ b/src/plugins/intel_npu/src/utils/src/zero/zero_wrappers.cpp
@@ -53,17 +53,16 @@ Event::~Event() {
     }
 }
 
-CommandList::CommandList(const ze_device_handle_t& device_handle,
-                         const ze_context_handle_t& context,
-                         ze_graph_dditable_ext_curr_t& graph_ddi_table_ext,
+CommandList::CommandList(const std::shared_ptr<ZeroInitStructsHolder>& initStructs,
                          const uint32_t& group_ordinal,
                          bool mtci_is_supported)
-    : _context(context),
-      _graph_ddi_table_ext(graph_ddi_table_ext),
+    : _initStructs(initStructs),
       _log("CommandList", Logger::global().level()) {
     ze_mutable_command_list_exp_desc_t mutable_desc = {ZE_STRUCTURE_TYPE_MUTABLE_COMMAND_LIST_EXP_DESC, nullptr, 0};
     ze_command_list_desc_t desc = {ZE_STRUCTURE_TYPE_COMMAND_LIST_DESC, &mutable_desc, group_ordinal, 0};
-    THROW_ON_FAIL_FOR_LEVELZERO("zeCommandListCreate", zeCommandListCreate(_context, device_handle, &desc, &_handle));
+    THROW_ON_FAIL_FOR_LEVELZERO(
+        "zeCommandListCreate",
+        zeCommandListCreate(_initStructs->getContext(), _initStructs->getDevice(), &desc, &_handle));
 
     if (mtci_is_supported) {
         ze_mutable_command_id_exp_desc_t mutableCmdIdDesc = {ZE_STRUCTURE_TYPE_MUTABLE_COMMAND_ID_EXP_DESC,
@@ -81,14 +80,15 @@ void CommandList::appendMemoryCopy(void* dst, const void* src, const std::size_t
                                 zeCommandListAppendMemoryCopy(_handle, dst, src, size, nullptr, 0, nullptr));
 }
 void CommandList::appendGraphInitialize(const ze_graph_handle_t& graph_handle) const {
-    ze_result_t result = _graph_ddi_table_ext.pfnAppendGraphInitialize(_handle, graph_handle, nullptr, 0, nullptr);
-    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnAppendGraphInitialize", result, _graph_ddi_table_ext);
+    ze_result_t result =
+        _initStructs->getGraphDdiTable().pfnAppendGraphInitialize(_handle, graph_handle, nullptr, 0, nullptr);
+    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnAppendGraphInitialize", result, _initStructs->getGraphDdiTable());
 }
 void CommandList::appendGraphExecute(const ze_graph_handle_t& graph_handle,
                                      const ze_graph_profiling_query_handle_t& profiling_query_handle) const {
-    ze_result_t result =
-        _graph_ddi_table_ext.pfnAppendGraphExecute(_handle, graph_handle, profiling_query_handle, nullptr, 0, nullptr);
-    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnAppendGraphExecute", result, _graph_ddi_table_ext);
+    ze_result_t result = _initStructs->getGraphDdiTable()
+                             .pfnAppendGraphExecute(_handle, graph_handle, profiling_query_handle, nullptr, 0, nullptr);
+    THROW_ON_FAIL_FOR_LEVELZERO_EXT("pfnAppendGraphExecute", result, _initStructs->getGraphDdiTable());
 }
 void CommandList::appendNpuTimestamp(uint64_t* timestamp_buff) const {
     THROW_ON_FAIL_FOR_LEVELZERO("zeCommandListAppendWriteGlobalTimestamp",
@@ -121,20 +121,17 @@ void CommandList::updateMutableCommandList(uint32_t arg_index, const void* arg_v
                                 zeCommandListUpdateMutableCommandsExp(_handle, &mutable_commands_exp_desc_t));
 }
 
-CommandQueue::CommandQueue(const ze_device_handle_t& device_handle,
-                           const ze_context_handle_t& context,
+CommandQueue::CommandQueue(const std::shared_ptr<ZeroInitStructsHolder>& initStructs,
                            const ze_command_queue_priority_t& priority,
-                           ze_command_queue_npu_dditable_ext_curr_t& command_queue_npu_dditable_ext,
-                           bool turbo,
-                           const uint32_t& group_ordinal)
-    : _context(context),
-      _command_queue_npu_dditable_ext(command_queue_npu_dditable_ext),
+                           const uint32_t& group_ordinal,
+                           bool turbo)
+    : _initStructs(initStructs),
       _log("CommandQueue", Logger::global().level()) {
     ze_command_queue_desc_t queue_desc =
         {ZE_STRUCTURE_TYPE_COMMAND_QUEUE_DESC, nullptr, group_ordinal, 0, 0, ZE_COMMAND_QUEUE_MODE_DEFAULT, priority};
 
     if (turbo) {
-        if (_command_queue_npu_dditable_ext.version()) {
+        if (_initStructs->getCommandQueueDdiTable().version()) {
             ze_command_queue_desc_npu_ext_t turbo_cfg = {ZE_STRUCTURE_TYPE_COMMAND_QUEUE_DESC_NPU_EXT, nullptr, turbo};
             queue_desc.pNext = &turbo_cfg;
         } else {
@@ -142,8 +139,9 @@ CommandQueue::CommandQueue(const ze_device_handle_t& device_handle,
         }
     }
 
-    THROW_ON_FAIL_FOR_LEVELZERO("zeCommandQueueCreate",
-                                zeCommandQueueCreate(_context, device_handle, &queue_desc, &_handle));
+    THROW_ON_FAIL_FOR_LEVELZERO(
+        "zeCommandQueueCreate",
+        zeCommandQueueCreate(_initStructs->getContext(), _initStructs->getDevice(), &queue_desc, &_handle));
 }
 void CommandQueue::executeCommandList(CommandList& command_list) const {
     THROW_ON_FAIL_FOR_LEVELZERO("zeCommandQueueExecuteCommandLists",
@@ -155,9 +153,9 @@ void CommandQueue::executeCommandList(CommandList& command_list, Fence& fence) c
 }
 
 void CommandQueue::setWorkloadType(ze_command_queue_workload_type_t workloadType) const {
-    if (_command_queue_npu_dditable_ext.version()) {
+    if (_initStructs->getCommandQueueDdiTable().version()) {
         THROW_ON_FAIL_FOR_LEVELZERO("zeSetWorkloadType",
-                                    _command_queue_npu_dditable_ext.pfnSetWorkloadType(_handle, workloadType));
+                                    _initStructs->getCommandQueueDdiTable().pfnSetWorkloadType(_handle, workloadType));
     } else {
         OPENVINO_THROW("The WorkloadType property is not supported by the current Driver Version!");
     }
diff --git a/src/plugins/intel_npu/tools/common/include/tensor_utils.hpp b/src/plugins/intel_npu/tools/common/include/tensor_utils.hpp
index 87b2301a7ae4fb..18d431c157d2dd 100644
--- a/src/plugins/intel_npu/tools/common/include/tensor_utils.hpp
+++ b/src/plugins/intel_npu/tools/common/include/tensor_utils.hpp
@@ -68,5 +68,13 @@ std::vector<std::vector<float>> parseTensorsAsFP32(const std::map<std::string, o
  * @return The merged batched tensor
  */
 ov::Tensor joinTensors(const std::list<ov::Tensor>& tensors, const ov::Layout& layout);
+
+/**
+ * @brief Split a batched tensor on several non-batched tensors having the same shapes and precisions.
+ *
+ * @param tensors The source non-batched tensors
+ * @return The merged batched tensor
+ */
+std::list<ov::Tensor> splitBatchedTensor(const ov::Tensor &tensor, const ov::Layout& layout, size_t parts);
 }  // namespace utils
 }  // namespace npu
diff --git a/src/plugins/intel_npu/tools/common/include/tools_helpers.hpp b/src/plugins/intel_npu/tools/common/include/tools_helpers.hpp
index e9743594ad8711..304f16c29d9a87 100644
--- a/src/plugins/intel_npu/tools/common/include/tools_helpers.hpp
+++ b/src/plugins/intel_npu/tools/common/include/tools_helpers.hpp
@@ -109,6 +109,7 @@ void setModelBatch(std::shared_ptr<ov::Model>& model, uint32_t batch = 1) {
     if (batch == 1) {
         return;
     }
+    std::cout << "Configuring model batch: " << batch << std::endl;
     for (auto&& item : model->get_parameters()) {
         auto shape = item->get_partial_shape();
         auto rank = shape.rank();
@@ -175,7 +176,20 @@ void reshape(ov::OutputVector inputsInfo, InputsInfo& infoMap, std::shared_ptr<o
             device.find("CPU") != std::string::npos || device.find("TEMPLATE") != std::string::npos) {
             boundDynamicShape(model);
         }
+    }
+}
 
-        setModelBatch(model, overrideModelBatchSize);
+void printInputAndOutputsInfoShort(const ov::Model& network) {
+    std::cout << "Network inputs:" << std::endl;
+    for (auto&& param : network.get_parameters()) {
+        auto l = param->get_layout();
+        std::cout << "    " << param->get_friendly_name() << " : " << param->get_element_type() << " / "
+                  << param->get_layout().to_string() << " / " << param->get_partial_shape().to_string() << std::endl;
+    }
+    std::cout << "Network outputs:" << std::endl;
+    for (auto&& result : network.get_results()) {
+        std::cout << "    " << result->get_friendly_name() << " : " << result->get_element_type() << " / "
+                  << result->get_layout().to_string() << " / " << result->get_output_partial_shape(0).to_string()
+                  << std::endl;
     }
 }
diff --git a/src/plugins/intel_npu/tools/common/src/tensor_utils.cpp b/src/plugins/intel_npu/tools/common/src/tensor_utils.cpp
index 32616b86135243..c2b4902497777e 100644
--- a/src/plugins/intel_npu/tools/common/src/tensor_utils.cpp
+++ b/src/plugins/intel_npu/tools/common/src/tensor_utils.cpp
@@ -492,5 +492,29 @@ ov::Tensor joinTensors(const std::list<ov::Tensor>& tensors, const ov::Layout& l
     }
     return out;
 }
+
+std::list<ov::Tensor> splitBatchedTensor(const ov::Tensor &tensor, const ov::Layout& layout, size_t parts) {
+    if (!parts) {
+        OPENVINO_THROW("Cannot split tensor on parts: ", parts);
+    }
+    auto pivotShape = tensor.get_shape();
+    if (!ov::layout::has_batch(layout)) {
+        OPENVINO_THROW("Cannot split tensor: has no batch_idx in layout", layout.to_string());
+    }
+    auto pivotPrecision = tensor.get_element_type();
+    if (pivotShape[ov::layout::batch_idx(layout)] % parts != 0) {
+        OPENVINO_THROW("Cannot split tensor with batch size: ", pivotShape[ov::layout::batch_idx(layout)], " on: ", parts ," equal tensors");
+    }
+    pivotShape[ov::layout::batch_idx(layout)] /= parts;
+    std::list<ov::Tensor> ret;
+    const auto *inputBuffer = tensor.data<unsigned char>();
+    for (size_t i = 0; i < parts; i ++) {
+        ov::Tensor out(pivotPrecision, pivotShape);
+        memcpy(out.data<unsigned char>(), inputBuffer, out.get_byte_size());
+        inputBuffer += out.get_byte_size();
+        ret.push_back(std::move(out));
+    }
+    return ret;
+}
 }  // namespace utils
 }  // namespace npu
diff --git a/src/plugins/intel_npu/tools/compile_tool/main.cpp b/src/plugins/intel_npu/tools/compile_tool/main.cpp
index 7a088d1afc69e2..47178833508182 100644
--- a/src/plugins/intel_npu/tools/compile_tool/main.cpp
+++ b/src/plugins/intel_npu/tools/compile_tool/main.cpp
@@ -296,21 +296,6 @@ void configurePrePostProcessing(std::shared_ptr<ov::Model>& model, const std::st
     model = preprocessor.build();
 }
 
-void printInputAndOutputsInfoShort(const ov::Model& network) {
-    std::cout << "Network inputs:" << std::endl;
-    for (auto&& param : network.get_parameters()) {
-        auto l = param->get_layout();
-        std::cout << "    " << param->get_friendly_name() << " : " << param->get_element_type() << " / "
-                  << param->get_layout().to_string() << " / " << param->get_partial_shape().to_string() << std::endl;
-    }
-    std::cout << "Network outputs:" << std::endl;
-    for (auto&& result : network.get_results()) {
-        std::cout << "    " << result->get_friendly_name() << " : " << result->get_element_type() << " / "
-                  << result->get_layout().to_string() << " / " << result->get_output_partial_shape(0).to_string()
-                  << std::endl;
-    }
-}
-
 inline std::string fileNameNoExt(const std::string& filepath) {
     auto pos = filepath.rfind('.');
     if (pos == std::string::npos)
@@ -456,6 +441,9 @@ int main(int argc, char* argv[]) {
         std::cout << "Configuring model pre & post processing" << std::endl;
         configurePrePostProcessing(model, FLAGS_ip, FLAGS_op, FLAGS_iop, FLAGS_il, FLAGS_ol, FLAGS_iol, FLAGS_iml,
                                    FLAGS_oml, FLAGS_ioml);
+        if (FLAGS_shape.empty()) {
+            setModelBatch(model, FLAGS_override_model_batch_size);
+        }
         std::cout << "Printing Input and Output Info from model" << std::endl;
         printInputAndOutputsInfoShort(*model);
         auto timeBeforeLoadNetwork = std::chrono::steady_clock::now();
diff --git a/src/plugins/intel_npu/tools/single-image-test/main.cpp b/src/plugins/intel_npu/tools/single-image-test/main.cpp
index 5658c18650243b..2454e9afd40e0d 100644
--- a/src/plugins/intel_npu/tools/single-image-test/main.cpp
+++ b/src/plugins/intel_npu/tools/single-image-test/main.cpp
@@ -183,6 +183,21 @@ std::vector<std::string> splitStringList(const std::string& str, char delim) {
     return out;
 }
 
+std::string to_string(const std::vector<std::string>& c) {
+    std::stringstream stream;
+    std::string ret;
+    if (!c.empty()) {
+        stream << "[";
+        for (const auto &elem : c) {
+            stream << elem << ",";
+        }
+        ret = stream.str();
+        ret.pop_back();
+        ret += "]";
+    }
+    return ret;
+}
+
 std::map<std::string, std::string> parseArgMap(std::string argMap) {
     argMap.erase(std::remove_if(argMap.begin(), argMap.end(), ::isspace), argMap.end());
 
@@ -386,7 +401,23 @@ void convertBufferType(OutT* destination, const InT* source, size_t numberOfElem
     });
 }
 
-void cvToOV(const cv::Mat& cvImg, const ov::Tensor& tensor, const ov::Shape& shape, const ov::Layout& layout,
+struct BatchIndexer {
+    const size_t index = 0;
+    const size_t size = 1;
+
+    BatchIndexer(size_t lineIndex = 0, size_t lineCount = 1) : index(lineIndex), size(lineCount) {
+        OPENVINO_ASSERT(index < size, "Inconsistent parameters used for "
+                        "BatchIndexer construction, lineIndex: ", index,
+                        " must be lesser than lineCount: ", size);
+    }
+
+    std::string to_string() const {
+        std::stringstream sstream;
+        sstream << "["  << index << "/" << size << "]";
+        return sstream.str();
+    }
+};
+void cvToOV(const cv::Mat& cvImg, const BatchIndexer &cvImgInBatch, const ov::Tensor& tensor, const ov::Shape& shape, const ov::Layout& layout,
             const std::string& colorFormat) {
     const ov::element::Type& precision = tensor.get_element_type();
 
@@ -449,8 +480,12 @@ void cvToOV(const cv::Mat& cvImg, const ov::Tensor& tensor, const ov::Shape& sha
 
     if (layout == ov::Layout("NHWC")) {
         const auto dataBuffer = reinterpret_cast<uint8_t*>(tensor.data());
-
-        cv::Mat out(static_cast<int>(H), static_cast<int>(W), cvType, dataBuffer);
+        cv::Mat auxOut(static_cast<int>(H), static_cast<int>(W), cvType);
+        cv::Mat tensorOut(static_cast<int>(H), static_cast<int>(W), cvType, dataBuffer);
+        // only a first image from an input image array fills an original input tensor up.
+        // Subsequent images (if exist) will fill batch slices of the input tensor
+        // by its number in the input array respectively
+        cv::Mat &out = (cvImgInBatch.index == 0 ? tensorOut : auxOut);
 
         if (precision == ov::element::Type_t::f16) {
             const auto inPtr = in.ptr<float>();
@@ -466,13 +501,35 @@ void cvToOV(const cv::Mat& cvImg, const ov::Tensor& tensor, const ov::Shape& sha
             in.copyTo(out);
         }
 
-        for (size_t n = 1; n < N; ++n) {
+        // Being called sequentially with ascending `cvImgInBatch.index` value,
+        // it fills up rest of the batched tensor by
+        // a last requested image data until its ending from a batched slice position
+        // determined by parameter 'cvImgInBatch.index', so that filling N batched tensor
+        // by array of images size M, where M < N, will make up
+        // The final batched tensor will comprise
+        // [imgIdx_0, imgIdx_1,..., imgIdx_M, imgIdx_M,...,imgIdx_M] as its slices
+        if (cvImgInBatch.index == 0 && N != 1) {
+            std::cout << "Fill up all input batch slices up to " << N
+                      << " with image data from the array: ["
+                      << cvImgInBatch.to_string() << std::endl;
+        }
+        for (size_t n = std::max<size_t>(1, cvImgInBatch.index); n < N; ++n) {
+            if (n == std::max<size_t>(1, cvImgInBatch.index) && cvImgInBatch.index >= 1) {
+                std::cout << "Fill input batch slices starting from index "
+                          << n << " up to " << N << " with image data from the array: "
+                          << cvImgInBatch.to_string() << std::endl;
+            }
             cv::Mat batch(static_cast<int>(H), static_cast<int>(W), cvType,
                           dataBuffer + n * (out.size().area() * out.elemSize()));
             out.copyTo(batch);
         }
     } else if (layout == ov::Layout("NCHW")) {
-        auto tensorPlanes = ovToCV(tensor, shape, layout, 0);
+        ov::Tensor auxTensor(precision, shape);
+        const ov::Tensor &outTensor = (cvImgInBatch.index == 0 ? tensor : auxTensor);
+        // only a first image from an input image array fills an original input tensor up.
+        // Subsequent images (if exist) will fill batch slices of the input tensor
+        // by its number in the input array respectively
+        auto tensorPlanes = ovToCV(outTensor, shape, layout, 0);
 
         if (!(precision == ov::element::Type_t::f16 ||
             precision == ov::element::Type_t::bf16)) {
@@ -495,7 +552,24 @@ void cvToOV(const cv::Mat& cvImg, const ov::Tensor& tensor, const ov::Shape& sha
             }
         }
 
-        for (size_t n = 1; n < N; ++n) {
+        // Being called sequentially with ascending `cvImgInBatch.index` value,
+        // it fills up rest of the batched tensor by
+        // a last requested image data until its ending from a batched slice position
+        // determined by parameter 'cvImgInBatch.index', so that filling N batched tensor
+        // by array of images size M, where M < N, will make up
+        // The final batched tensor will comprise
+        // [imgIdx_0, imgIdx_1,..., imgIdx_M, imgIdx_M,...,imgIdx_M] as its slices
+        if (cvImgInBatch.index == 0 && N != 1) {
+            std::cout << "Fill up all input batch slices planes up to " << N
+                      << " with image data from the array: "
+                      << cvImgInBatch.to_string() << std::endl;
+        }
+        for (size_t n = std::max<size_t>(1, cvImgInBatch.index); n < N; ++n) {
+            if (n == std::max<size_t>(1, cvImgInBatch.index) && cvImgInBatch.index >= 1) {
+                std::cout << "Fill input batch slices planes starting from index "
+                          << n << " up to " << N << " with image data from the array: "
+                          << cvImgInBatch.to_string() << std::endl;
+            }
             const auto batchPlanes = ovToCV(tensor, shape, layout, n);
 
             OPENVINO_ASSERT(batchPlanes.size() == tensorPlanes.size());
@@ -654,27 +728,28 @@ std::string cleanName(std::string&& name) {
     return std::move(name);
 }
 
-ov::Tensor loadImage(const ov::element::Type& precision, const ov::Shape& shape, const ov::Layout& layout,
-                     const std::string& filePath, const std::string& colorFormat) {
-    const auto frame = cv::imread(filePath, cv::IMREAD_COLOR);
-    OPENVINO_ASSERT(!frame.empty(), "Failed to open input image file ", filePath);
-
+ov::Tensor loadImages(const ov::element::Type& precision, const ov::Shape& shape, const ov::Layout& layout,
+                     const std::vector<std::string>& filePaths, const std::string& colorFormat) {
     const ov::Tensor tensor(precision, shape);
+    for (size_t fileIndex = 0; fileIndex != filePaths.size(); fileIndex++) {
+        const auto &filePath = filePaths[fileIndex];
+        const auto frame = cv::imread(filePath, cv::IMREAD_COLOR);
+        OPENVINO_ASSERT(!frame.empty(), "Failed to open input image file ", filePath);
 
-    cvToOV(frame, tensor, shape, layout, colorFormat);
-
+        cvToOV(frame, BatchIndexer{fileIndex, filePaths.size()}, tensor, shape, layout, colorFormat);
+    }
     return tensor;
 }
 
-ov::Tensor loadBinary(const ov::element::Type& modelPrecision, const ov::Shape& shape, const ov::Layout& layout,
-                      const std::string& filePath, const ov::element::Type& dataPrecision) {
+void loadBinary(const std::string& filePath, const BatchIndexer &fileSourceInBatch, ov::Tensor &requestedTensor,
+                const ov::element::Type& modelPrecision, const ov::Shape& shape,
+                const ov::Layout& layout, const ov::element::Type& dataPrecision) {
     std::ifstream binaryFile(filePath, std::ios_base::binary | std::ios_base::ate);
     OPENVINO_ASSERT(binaryFile, "Failed to open input binary file: ", filePath);
     const auto fileSize = binaryFile.tellg();
     binaryFile.seekg(0, std::ios_base::beg);
     OPENVINO_ASSERT(binaryFile.good(), "While reading a file an error is encountered");
     const size_t fileBytes = static_cast<size_t>(fileSize);
-    ov::Tensor requestedTensor(modelPrecision, shape);
     const size_t reqTensorBytes = static_cast<size_t>(requestedTensor.get_byte_size());
 
     if (dataPrecision != modelPrecision && dataPrecision != ov::element::Type_t::undefined) {
@@ -688,7 +763,7 @@ ov::Tensor loadBinary(const ov::element::Type& modelPrecision, const ov::Shape&
             std::cout << "File contains " << fileBytes
                       << " bytes, but it expected to be: " << inputTensor.get_byte_size()
                       << " while converting precision from " << dataPrecision << " to " << modelPrecision
-                      << ". Check whether it is possible to batch loading " << std::endl;
+                      << ". Check whether it is possible to fit it into batch loading " << std::endl;
             OPENVINO_ASSERT(ov::layout::has_batch(layout),
                             "Input layout has no batch dimenstion: ", layout.to_string());
             size_t N = shape[ov::layout::batch_idx(layout)];
@@ -703,12 +778,20 @@ ov::Tensor loadBinary(const ov::element::Type& modelPrecision, const ov::Shape&
             const ov::Tensor convertedPrecisionTensor(modelPrecision, debatchedInputTensorShape);
             npu::utils::convertTensorPrecision(inputDebatchedTensor, convertedPrecisionTensor);
             std::list<ov::Tensor> tensorsToJoin;
-            std::generate_n(std::back_inserter(tensorsToJoin), N, [&convertedPrecisionTensor]() {
-                return convertedPrecisionTensor;
-            });
+            std::list<ov::Tensor> tensorsFromSplit = npu::utils::splitBatchedTensor(requestedTensor, layout, N);
+            // Constitute a new bathed tensor of size N from parts of it
+            // enumerated by indices from the interval [0...fileSourceInBatch.index],
+            // where fileSourceInBatch.index < N
+            // The rest parts of the new tensor [fileSourceInBatch.index+1...N]
+            // will be filled up by same content of an image of `fileSourceInBatch.index`
+            std::copy_n(tensorsFromSplit.begin(), std::min(fileSourceInBatch.index, N), std::back_inserter(tensorsToJoin));
+            if (fileSourceInBatch.index < N) {
+                std::generate_n(std::back_inserter(tensorsToJoin), N - fileSourceInBatch.index, [&convertedPrecisionTensor]() {
+                    return convertedPrecisionTensor;
+                });
+            }
             requestedTensor = npu::utils::joinTensors(tensorsToJoin, layout);
         }
-
     } else {
         if (fileBytes == reqTensorBytes) {
             binaryFile.read(reinterpret_cast<char*>(requestedTensor.data()),
@@ -716,22 +799,40 @@ ov::Tensor loadBinary(const ov::element::Type& modelPrecision, const ov::Shape&
         } else {
             std::cout << "File contains " << fileBytes << " bytes, but it expected to be: " << reqTensorBytes
                       << " when datatypes match. "
-                      << ". Check whether it is possible to batch loading " << std::endl;
+                      << "Check whether it is possible to fit it into batch loading " << std::endl;
             OPENVINO_ASSERT(ov::layout::has_batch(layout),
                             "Input layout has no batch dimenstion: ", layout.to_string());
             size_t N = shape[ov::layout::batch_idx(layout)];
             OPENVINO_ASSERT(fileBytes * N == reqTensorBytes, "File contains ", fileBytes, " bytes, but ",
                             reqTensorBytes, " in batch size ", N, " expected");
 
-            // duplicate a binary into tensor memory if the tensor batched
-            for (size_t n = 0; n < N; ++n) {
+            if (fileSourceInBatch.index == 0 && N != 1) {
+                std::cout << "Fill up all input batch slices up to " << N
+                          << " with binary data from the array: "
+                          << fileSourceInBatch.to_string() << std::endl;
+            }
+            for (size_t n = std::max<size_t>(0, fileSourceInBatch.index); n < N; ++n) {
+                if (n == std::max<size_t>(1, fileSourceInBatch.index) && fileSourceInBatch.index >= 1) {
+                    std::cout << "Fill input batch slices starting from index "
+                              << n << " up to " << N
+                              << " with binary data from the data sources array: "
+                              << fileSourceInBatch.to_string() << std::endl;
+                }
                 binaryFile.seekg(0, std::ios_base::beg);
                 binaryFile.read(reinterpret_cast<char*>(requestedTensor.data()) + fileBytes * n,
                                 static_cast<std::streamsize>(fileBytes));
             }
         }
     }
+}
 
+ov::Tensor loadBinaries(const ov::element::Type& modelPrecision, const ov::Shape& shape, const ov::Layout& layout,
+                      const std::vector<std::string>& filePaths, const ov::element::Type& dataPrecision) {
+    ov::Tensor requestedTensor(modelPrecision, shape);
+    for (size_t fileIndex = 0; fileIndex != filePaths.size(); fileIndex++) {
+        const auto &filePath = filePaths[fileIndex];
+        loadBinary(filePath, BatchIndexer{fileIndex, filePaths.size()}, requestedTensor, modelPrecision, shape, layout, dataPrecision);
+    }
     return requestedTensor;
 }
 
@@ -752,12 +853,12 @@ ov::Tensor loadBinary(const ov::element::Type& modelPrecision, const ov::Shape&
  * @return The tensor containing the loaded data.
  */
 ov::Tensor loadInput(const ov::element::Type& modelPrecision, const ov::Shape& shape, const ov::Layout& layout,
-                     const std::string& filePath, const std::string& colorFormat,
+                     const std::vector<std::string>& filePaths, const std::string& colorFormat,
                      const ov::element::Type& dataPrecision = ov::element::Type_t::undefined) {
     if (isImage(shape, layout) && !FLAGS_img_as_bin) {
-        return loadImage(modelPrecision, shape, layout, filePath, colorFormat);
+        return loadImages(modelPrecision, shape, layout, filePaths, colorFormat);
     } else {
-        return loadBinary(modelPrecision, shape, layout, filePath, dataPrecision);
+        return loadBinaries(modelPrecision, shape, layout, filePaths, dataPrecision);
     }
 }
 
@@ -1719,11 +1820,20 @@ static int runSingleImageTest() {
         std::map<RegexPtr, ov::Layout> outModelLayouts = parseLayoutRegex(FLAGS_oml);
 
         std::vector<std::string> inputFilesPerCase;
-        std::vector<std::vector<std::string>> inputFilesForOneInfer;
+        using FilesPerInput = std::vector<std::string>;
+        using FilesForModelInputs = std::vector<FilesPerInput>;
+        std::vector<FilesForModelInputs> inputFilesForOneInfer;
 
         inputFilesPerCase = splitStringList(FLAGS_input, ';');
         for (const auto& images : inputFilesPerCase) {
-            inputFilesForOneInfer.push_back(splitStringList(images, ','));
+            std::vector<std::string> filesPerModel = splitStringList(images, ',');
+            FilesForModelInputs entireModelFiles;
+            entireModelFiles.reserve(filesPerModel.size());
+            for (auto &&filesPerInput : filesPerModel) {
+                // from now on each input of a model support multiple image files as content of a batched input
+                entireModelFiles.push_back(splitStringList(filesPerInput, '|'));
+            }
+            inputFilesForOneInfer.push_back(std::move(entireModelFiles));
         }
 
         std::vector<std::string> inputBinPrecisionStrPerCase;
@@ -1896,8 +2006,13 @@ static int runSingleImageTest() {
                 }
             }
 
+            if (FLAGS_shape.empty()) {
+                setModelBatch(model, FLAGS_override_model_batch_size);
+            }
             std::cout << "Compile model" << std::endl;
-            compiledModel = core.compile_model(ppp.build(), FLAGS_device);
+            model = ppp.build();
+            printInputAndOutputsInfoShort(*model);
+            compiledModel = core.compile_model(model, FLAGS_device);
         } else {
             std::cout << "Import network " << FLAGS_network << std::endl;
 
@@ -1947,7 +2062,7 @@ static int runSingleImageTest() {
         for (size_t numberOfTestCase = 0; numberOfTestCase < inputFilesPerCase.size(); ++numberOfTestCase) {
             const auto inputsInfo = compiledModel.inputs();
             const auto outputsInfo = compiledModel.outputs();
-            std::vector<std::string> inputFiles = inputFilesForOneInfer[numberOfTestCase];
+            const FilesForModelInputs &inputFiles = inputFilesForOneInfer[numberOfTestCase];
             OPENVINO_ASSERT(inputFiles.size() == inputsInfo.size(), "Number of input files ", inputFiles.size(),
                             " doesn't match network configuration ", inputsInfo.size());
 
@@ -1984,7 +2099,7 @@ static int runSingleImageTest() {
                 inputDescriptors.emplace(inputInfo.get_any_name(), TensorDescriptor{precision, shape,
                                                                                     dataShape, inputLayout});
 
-                std::cout << "Load input #" << inputInd << " from " << inputFiles[inputInd] << " as " << precision
+                std::cout << "Load input #" << inputInd << " from " << to_string(inputFiles[inputInd]) << " as " << precision
                           << " " << inputLayout.to_string() << " " << shape << std::endl;
 
                 const ov::Tensor tensor =
diff --git a/src/plugins/template/backend/ops/identity.cpp b/src/plugins/template/backend/ops/identity.cpp
new file mode 100644
index 00000000000000..184885e6a3330e
--- /dev/null
+++ b/src/plugins/template/backend/ops/identity.cpp
@@ -0,0 +1,22 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/reference/identity.hpp"
+
+#include "evaluate_node.hpp"
+#include "openvino/core/type/element_iterator.hpp"
+
+template <>
+bool evaluate_node<ov::op::v16::Identity>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
+    const auto input_shape = inputs[0].get_shape();
+
+    outputs[0].set_shape(input_shape);
+
+    ov::reference::identity(static_cast<const char*>(inputs[0].data()),
+                            static_cast<char*>(outputs[0].data()),
+                            inputs[0].get_byte_size());
+    return true;
+}
diff --git a/src/plugins/template/backend/ops/ops_evaluates.hpp b/src/plugins/template/backend/ops/ops_evaluates.hpp
index e63c7aa8b4f9e4..18a904385411b0 100644
--- a/src/plugins/template/backend/ops/ops_evaluates.hpp
+++ b/src/plugins/template/backend/ops/ops_evaluates.hpp
@@ -550,3 +550,7 @@ extern template bool evaluate_node<ov::op::v15::StringTensorPack>(std::shared_pt
 extern template bool evaluate_node<ov::op::v15::SearchSorted>(std::shared_ptr<ov::Node> node,
                                                               ov::TensorVector& outputs,
                                                               const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v16::Identity>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
diff --git a/src/plugins/template/backend/opset_int_tbl.hpp b/src/plugins/template/backend/opset_int_tbl.hpp
index 42dfa2797031f1..44c1a1b085e878 100644
--- a/src/plugins/template/backend/opset_int_tbl.hpp
+++ b/src/plugins/template/backend/opset_int_tbl.hpp
@@ -164,7 +164,6 @@ _OPENVINO_OP_REG(AvgPool, ov::op::v14)
 _OPENVINO_OP_REG(MaxPool, ov::op::v14)
 
 _OPENVINO_OP_REG(ROIAlignRotated, ov::op::v15)
-
 _OPENVINO_OP_REG(EmbeddingBagOffsets, op::v15)
 _OPENVINO_OP_REG(EmbeddingBagPacked, op::v15)
 _OPENVINO_OP_REG(Col2Im, ov::op::v15)
@@ -176,6 +175,8 @@ _OPENVINO_OP_REG(BitwiseRightShift, ov::op::v15)
 _OPENVINO_OP_REG(SliceScatter, ov::op::v15)
 _OPENVINO_OP_REG(SearchSorted, ov::op::v15)
 
+_OPENVINO_OP_REG(Identity, ov::op::v16)
+
 _OPENVINO_OP_REG(AUGRUCell, ov::op::internal)
 _OPENVINO_OP_REG(AUGRUSequence, ov::op::internal)
 _OPENVINO_OP_REG(RMS, ov::op::internal)
diff --git a/src/plugins/template/src/plugin.cpp b/src/plugins/template/src/plugin.cpp
index ee885f67e188b5..f66df99c7b1c43 100644
--- a/src/plugins/template/src/plugin.cpp
+++ b/src/plugins/template/src/plugin.cpp
@@ -221,6 +221,7 @@ ov::SupportedOpsMap ov::template_plugin::Plugin::query_model(const std::shared_p
 #include "openvino/opsets/opset13_tbl.hpp"
 #include "openvino/opsets/opset14_tbl.hpp"
 #include "openvino/opsets/opset15_tbl.hpp"
+#include "openvino/opsets/opset16_tbl.hpp"
         // clang-format on
 #undef _OPENVINO_OP_REG
             return op_super_set.contains_type(node->get_type_info());
diff --git a/src/plugins/template/tests/functional/op_reference/identity.cpp b/src/plugins/template/tests/functional/op_reference/identity.cpp
new file mode 100644
index 00000000000000..970b61ef0dfcdb
--- /dev/null
+++ b/src/plugins/template/tests/functional/op_reference/identity.cpp
@@ -0,0 +1,92 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/identity.hpp"
+
+#include "base_reference_test.hpp"
+#include "gtest/gtest.h"
+#include "openvino/op/parameter.hpp"
+
+namespace {
+using IdentityParams = std::tuple<reference_tests::Tensor, std::string>;
+
+class ReferenceIdentity : public testing::TestWithParam<IdentityParams>, public reference_tests::CommonReferenceTest {
+public:
+    void SetUp() override {
+        const auto& params = GetParam();
+        const auto& matrices = std::get<0>(params);
+        function = CreateFunction(params);
+        inputData = {matrices.data};
+        refOutData = {matrices.data};
+    }
+
+    static std::string getTestCaseName(const testing::TestParamInfo<IdentityParams>& obj) {
+        std::ostringstream name;
+        const auto& matrices = std::get<0>(obj.param);
+        name << std::get<1>(obj.param);
+        name << "_input_type_";
+        name << matrices.type;
+        name << "_shape_";
+        name << matrices.shape;
+        return name.str();
+    }
+
+private:
+    static std::shared_ptr<ov::Model> CreateFunction(const IdentityParams& params) {
+        const auto& matrices = std::get<0>(params);
+        const auto in_matrices = std::make_shared<ov::op::v0::Parameter>(matrices.type, matrices.shape);
+        const auto identity = std::make_shared<ov::op::v16::Identity>(in_matrices);
+        return std::make_shared<ov::Model>(identity->outputs(), ov::ParameterVector{in_matrices});
+    }
+};
+
+template <ov::element::Type_t ET>
+std::vector<IdentityParams> generateIdentityParams() {
+    using VT = typename ov::element_type_traits<ET>::value_type;
+
+    const ov::Shape matrices_2_2_shape{2, 2};
+    const ov::Shape matrices_2_3_3_shape{2, 3, 3};
+
+    reference_tests::Tensor matrices_2_2(matrices_2_2_shape, ET, std::vector<VT>{1, 2, 4, 5});
+
+    reference_tests::Tensor matrices_2_3_3(matrices_2_3_3_shape,
+                                           ET,
+                                           std::vector<VT>{1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 8, 7, 4, 5, 3, 1, 2, 6});
+
+    std::vector<IdentityParams> params;
+    params.emplace_back(matrices_2_2, "single");
+    params.emplace_back(matrices_2_3_3, "many");
+
+    return params;
+}
+
+std::vector<IdentityParams> generateIdentityParams() {
+    std::vector<std::vector<IdentityParams>> combo_params{generateIdentityParams<ov::element::boolean>(),
+                                                          generateIdentityParams<ov::element::bf16>(),
+                                                          generateIdentityParams<ov::element::f16>(),
+                                                          generateIdentityParams<ov::element::f64>(),
+                                                          generateIdentityParams<ov::element::f32>(),
+                                                          generateIdentityParams<ov::element::i8>(),
+                                                          generateIdentityParams<ov::element::i16>(),
+                                                          generateIdentityParams<ov::element::i32>(),
+                                                          generateIdentityParams<ov::element::i64>(),
+                                                          generateIdentityParams<ov::element::u8>(),
+                                                          generateIdentityParams<ov::element::u16>(),
+                                                          generateIdentityParams<ov::element::u32>(),
+                                                          generateIdentityParams<ov::element::u64>()};
+    std::vector<IdentityParams> test_params;
+    for (auto& params : combo_params)
+        std::move(params.begin(), params.end(), std::back_inserter(test_params));
+    return test_params;
+}
+}  // namespace
+
+TEST_P(ReferenceIdentity, CompareWithRefs) {
+    Exec();
+}
+
+INSTANTIATE_TEST_SUITE_P(smoke,
+                         ReferenceIdentity,
+                         ::testing::ValuesIn(generateIdentityParams()),
+                         ReferenceIdentity::getTestCaseName);
diff --git a/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp b/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp
index fb192e0ac40223..2e997dee2ba7b9 100644
--- a/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp
+++ b/src/tests/functional/plugin/conformance/test_runner/op_conformance_runner/src/op_impl_check/single_op_graph.cpp
@@ -525,6 +525,13 @@ std::shared_ptr<ov::Model> generate(const std::shared_ptr<ov::op::v0::Interpolat
     return std::make_shared<ov::Model>(results, params, "Interpolat-1");
 }
 
+std::shared_ptr<ov::Model> generate(const std::shared_ptr<ov::op::v16::Identity>& node) {
+    ov::ParameterVector params{std::make_shared<ov::op::v0::Parameter>(ov::element::f32, ov::Shape{4, 4, 4})};
+    const auto identity = std::make_shared<ov::op::v16::Identity>(params[0]);
+    ov::ResultVector results{std::make_shared<ov::op::v0::Result>(identity)};
+    return std::make_shared<ov::Model>(results, params, "Identity");
+}
+
 std::shared_ptr<ov::Model> generate(const std::shared_ptr<ov::op::v4::Interpolate> &node) {
     using InterpolateAttrs = op::v4::Interpolate::InterpolateAttrs;
     using InterpolateMode = op::v4::Interpolate::InterpolateMode;
@@ -2189,6 +2196,7 @@ OpGenerator getOpGeneratorMap() {
 #include "openvino/opsets/opset13_tbl.hpp"
 #include "openvino/opsets/opset14_tbl.hpp"
 #include "openvino/opsets/opset15_tbl.hpp"
+#include "openvino/opsets/opset16_tbl.hpp"
 #undef _OPENVINO_OP_REG
     };
     return opGeneratorMap;
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/identity.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/identity.hpp
new file mode 100644
index 00000000000000..5ad551569fdf17
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/identity.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/identity.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(IdentityLayerTest, Inference) {
+    run();
+};
+}  // namespace test
+}  // namespace ov
diff --git a/tests/layer_tests/py_frontend_tests/test_torch_frontend.py b/tests/layer_tests/py_frontend_tests/test_torch_frontend.py
index faee72bb5d938a..b659c1735d8453 100644
--- a/tests/layer_tests/py_frontend_tests/test_torch_frontend.py
+++ b/tests/layer_tests/py_frontend_tests/test_torch_frontend.py
@@ -687,6 +687,7 @@ def test_patched_16bit_model_converts():
     from openvino.frontend.pytorch import patch_model
     from openvino import convert_model, compile_model
     import copy
+    import inspect
     from transformers.pytorch_utils import Conv1D
 
     class ModelWithLinear(torch.nn.Module):
@@ -716,6 +717,9 @@ def forward(self, x1, x2):
     model_fp16 = copy.deepcopy(model_ref).half()
 
     patch_model.__make_16bit_traceable(model_fp16)
+    # verify torch.nn.Linear signature after patching
+    signature = inspect.signature(model_ref.branch1[0].forward).parameters
+    assert ["input"] == list(signature)
     # the approach with patching only works for node with no grad
     with torch.no_grad():
         converted_model = convert_model(model_fp16, example_input=example)
diff --git a/tools/benchmark_tool/openvino/tools/benchmark/main.py b/tools/benchmark_tool/openvino/tools/benchmark/main.py
index ad2839d217fcad..c77b50a7fd4721 100644
--- a/tools/benchmark_tool/openvino/tools/benchmark/main.py
+++ b/tools/benchmark_tool/openvino/tools/benchmark/main.py
@@ -49,6 +49,9 @@ def arg_not_empty(arg_value,empty_value):
         raise Exception("Cannot set precision for a compiled model. " \
                         "Please re-compile your model with required precision.")
 
+    if args.api_type == "sync" and args.number_infer_requests > args.number_iterations:
+        raise Exception("Number of infer requests should be less than or equal to number of iterations in sync mode.")
+
     return args, is_network_compiled
 
 def main():