diff --git a/python/tvm/tpat/cuda/kernel.py b/python/tvm/tpat/cuda/kernel.py
index a1a6c57f57adb..80877d4892e9f 100644
--- a/python/tvm/tpat/cuda/kernel.py
+++ b/python/tvm/tpat/cuda/kernel.py
@@ -15,6 +15,8 @@
 # specific language governing permissions and limitations
 # under the License.
 
+import os
+
 import tvm
 import tvm.contrib.graph_executor as runtime
 import tvm.relay as relay
@@ -86,7 +88,7 @@ def run(self):
         mod, params = relay.frontend.from_onnx(self._config.onnx_model)
 
         # 2. Tune it
-        if self._enable_tunning:
+        if self._enable_tunning and not os.path.exists(self._config.work_dir):
             tunning_option = self._config._tune_option()
             ms.relay_integration.tune_relay(mod=mod, params=params, **tunning_option)
 
diff --git a/python/tvm/tpat/cuda/onnx_util.py b/python/tvm/tpat/cuda/onnx_util.py
index 2c2fa5b702f29..dd2ef1ab0c333 100644
--- a/python/tvm/tpat/cuda/onnx_util.py
+++ b/python/tvm/tpat/cuda/onnx_util.py
@@ -90,9 +90,14 @@ def _handle_trt_not_support_type(
         _remove_unnecessary_cast_nodes(graph)
 
     try:
-        onnx.save(gs.export_onnx(graph), output_model_path)
+        onnx.save(gs.export_onnx(graph), output_model_path["name"])
     except:
-        onnx.save(gs.export_onnx(graph), output_model_path, save_as_external_data=True)
+        onnx.save(
+            gs.export_onnx(graph),
+            output_model_path["name"],
+            save_as_external_data=True,
+            location=output_model_path["weights"],
+        )
 
 
 def _remove_unnecessary_cast_nodes(graph):
diff --git a/python/tvm/tpat/cuda/pipeline.py b/python/tvm/tpat/cuda/pipeline.py
index 45ca7747d9e44..5bdcf31ed6234 100644
--- a/python/tvm/tpat/cuda/pipeline.py
+++ b/python/tvm/tpat/cuda/pipeline.py
@@ -119,7 +119,7 @@ def pipeline(
     node_names: list[str],
     enable_tunning: bool,
     tunning_option: object,
-    output_onnx: str,
+    output_onnx: object,
 ) -> Tuple[str, list[str]]:
     """Generate plugins for specified nodes in an ONNX model.
 
@@ -135,8 +135,11 @@ def pipeline(
         Flag indicating whether tunning is enabled.
     tunning_option : object
         Tunning option provided for ms.relay_integration.tune_relay, you don't need to specify mod, params and target.
-    output_onnx : str
+    output_onnx : object
+        { "name": xx, "weights": xx }
         Path to the output ONNX file where the modified model will be saved.
+        It will firstly try to save without weights, if it fails, it will then
+        save it with weights.
 
     Returns
     -------