diff --git a/userbenchmark/dynamo/dynamobench/common.py b/userbenchmark/dynamo/dynamobench/common.py
index d3ca51e8f4..cd0b98d4f4 100644
--- a/userbenchmark/dynamo/dynamobench/common.py
+++ b/userbenchmark/dynamo/dynamobench/common.py
@@ -703,6 +703,23 @@ def speedup_experiment_ds(args, model_iter_fn, model, example_inputs):
     return output_str
 
 
+@contextlib.contextmanager
+def override_synchronize_with_onnx_iobinding(iobinding):
+    global synchronize
+    prev_synchrnoize = synchronize
+    try:
+        if iobinding is not None:
+
+            def new_synchronize():
+                iobinding.synchronize_inputs()
+                iobinding.synchronize_outputs()
+
+            synchronize = new_synchronize
+        yield
+    finally:
+        synchronize = prev_synchrnoize
+
+
 def speedup_experiment_onnx(
     args,
     model_iter_fn,
@@ -737,7 +754,7 @@ def onnxrt_model_iter_fn(model, inputs, collect_outputs=True):
             if collect_outputs:
                 return outputs
 
-        return onnxrt_model_iter_fn
+        return onnxrt_model_iter_fn, iobinding
 
     def create_onnx_fn(onnx_model: OnnxModel, pt_inputs):
         # NOTE: Making perf comparison fair by moving out the i/o adapting part.
@@ -753,18 +770,20 @@ def onnxrt_model_iter_fn(model, inputs, collect_outputs=True):
     def timed_onnx(model, onnx_model: OnnxModel, inputs):
         if current_device == "cpu" or onnx_model.is_cpu():
             onnxrt_model_iter_fn = create_onnx_fn(onnx_model, inputs)
+            iobinding = None
         else:
-            onnxrt_model_iter_fn = create_onnx_input_binded_fn(
+            onnxrt_model_iter_fn, iobinding = create_onnx_input_binded_fn(
                 onnx_model, inputs, expected_output
             )
-        return timed(
-            model,
-            onnxrt_model_iter_fn,
-            inputs,
-            return_result=True,
-            times=times,
-            collect_outputs=args.collect_outputs,
-        )
+        with override_synchronize_with_onnx_iobinding(iobinding):
+            return timed(
+                model,
+                onnxrt_model_iter_fn,
+                inputs,
+                return_result=True,
+                times=times,
+                collect_outputs=args.collect_outputs,
+            )
 
     # Insert ONNX warm-up
     inputs = (