diff --git a/model-optimizer/extensions/middle/EltwiseInputReshape.py b/model-optimizer/extensions/middle/EltwiseInputReshape.py
index bd834f46ea2f32..7ddbfe1b6dad73 100644
--- a/model-optimizer/extensions/middle/EltwiseInputReshape.py
+++ b/model-optimizer/extensions/middle/EltwiseInputReshape.py
@@ -69,7 +69,6 @@ def find_and_replace_pattern(self, graph: Graph):
 class EltwiseInputReshape(MiddleReplacementPattern):
     # This pass should be called directly from pipeline before layout change and other permutations
     enabled = False
-    force_shape_inference = True
 
     def find_and_replace_pattern(self, graph: Graph):
         # Generate a map for producers of eltwise nodes with non-normalized shapes
@@ -97,11 +96,21 @@ def find_and_replace_pattern(self, graph: Graph):
             for unsqueeze_dims in mapping[producer_port].keys():
                 unsqueeze_name = producer_node.soft_get('name', producer_node.id) + '/EltwiseReshape'
                 unsqueeze_node = create_op_with_const_inputs(graph, Unsqueeze, {1: int64_array(list(unsqueeze_dims))},
-                                                             {'name': unsqueeze_name,
-                                                              'override_output_shape': True})
+                                                             {'name': unsqueeze_name})
 
                 unsqueeze_node.in_port(0).connect(producer_port)
 
                 # Insert Reshape with determined output shape between the current producer and eltwise node
                 for consumer_port in mapping[producer_port][unsqueeze_dims]:
                     consumer_port.connect(unsqueeze_node.out_port(0))
+
+                # The shape and value adjustments must be explicitly done within the transformation
+                # since the transformation is called from Fusing transformation that excludes
+                # automatic call of shape inference pass
+                producer_port_value = producer_port.data.get_value()
+                producer_port_shape = producer_port.data.get_shape()
+                new_shape = np.insert(producer_port_shape, np.zeros_like(unsqueeze_dims), 1)
+                if producer_port_value is not None:
+                    unsqueeze_node.out_port(0).data.set_value(np.reshape(producer_port_value, new_shape))
+                else:
+                    unsqueeze_node.out_port(0).data.set_shape(new_shape)
diff --git a/model-optimizer/extensions/middle/EltwiseInputReshape_test.py b/model-optimizer/extensions/middle/EltwiseInputReshape_test.py
index 1da0c56bdbfabb..8b8a0451b52274 100644
--- a/model-optimizer/extensions/middle/EltwiseInputReshape_test.py
+++ b/model-optimizer/extensions/middle/EltwiseInputReshape_test.py
@@ -20,7 +20,6 @@
 
 from extensions.middle.EltwiseInputReshape import EltwiseInputReshape
 from mo.front.common.partial_infer.utils import int64_array
-from mo.middle.passes.eliminate import shape_inference
 from mo.middle.passes.eliminate_test import build_graph
 from mo.utils.ir_engine.compare_graphs import compare_graphs
 
@@ -86,7 +85,6 @@ def test1_not_constant(self):
                              'placeholder_3_data': {'shape': np.array([64, 1])},
                              'eltwise_1_data': {'shape': np.array([1, 3, 64, 64])}
                              }, nodes_with_edges_only=True)
-        shape_inference(graph)
 
         graph_ref = build_graph(nodes_attributes,
                                 [
@@ -120,7 +118,6 @@ def test1_not_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'eltwise_1', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -216,7 +213,6 @@ def test_mega_hardcore(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'eltwise_4', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -278,7 +274,6 @@ def test2_not_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -334,7 +329,6 @@ def test3_not_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -397,7 +391,6 @@ def test4_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -451,7 +444,6 @@ def test5_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
         self.assertTrue(flag, resp)
@@ -495,7 +487,6 @@ def test6_not_constant(self):
 
         pattern = EltwiseInputReshape()
         pattern.find_and_replace_pattern(graph)
-        shape_inference(graph)
 
         (flag, resp) = compare_graphs(graph, graph_ref, 'concat', check_op_attrs=True)
         self.assertTrue(flag, resp)