diff --git a/py/torch_tensorrt/dynamo/_refit.py b/py/torch_tensorrt/dynamo/_refit.py
index 43fdecbf73..2b3ddce96e 100644
--- a/py/torch_tensorrt/dynamo/_refit.py
+++ b/py/torch_tensorrt/dynamo/_refit.py
@@ -37,7 +37,6 @@
 from torch_tensorrt.dynamo.runtime._TRTEngine import TRTEngine
 from torch_tensorrt.dynamo.utils import (
     check_module_output,
-    check_output_equal,
     get_torch_inputs,
     to_torch_device,
     to_torch_tensorrt_device,
@@ -436,31 +435,15 @@ def refit_module_weights(
 
     if verify_output and arg_inputs is not None:
         new_gm.to(to_torch_device(settings.device))  # move to device for inference
-        # complex_graph_detection rewrites complex placeholders to real (view_as_real).
-        # The compiled TRT module handles complex→real internally, but the lowered
-        # PyTorch reference module (new_gm) expects real-unpacked inputs directly.
-        has_complex_inputs = any(
-            isinstance(x, torch.Tensor) and x.is_complex() for x in torch_inputs
+        # A complex placeholder stays complex in the lowered reference module; the
+        # unpacking to real happens inside the graph, so both modules take the same
+        # inputs the caller passed.
+        outputs_match = check_module_output(
+            new_module=new_gm,
+            refitted_module=compiled_module,
+            arg_inputs=torch_inputs,
+            kwarg_inputs=torch_kwarg_inputs,
         )
-        if has_complex_inputs:
-            lowered_inputs = [
-                (
-                    torch.view_as_real(x).contiguous()
-                    if isinstance(x, torch.Tensor) and x.is_complex()
-                    else x
-                )
-                for x in torch_inputs
-            ]
-            trt_outputs = compiled_module(*torch_inputs)
-            ref_outputs = new_gm(*lowered_inputs, **torch_kwarg_inputs)
-            outputs_match = check_output_equal(trt_outputs, ref_outputs)
-        else:
-            outputs_match = check_module_output(
-                new_module=new_gm,
-                refitted_module=compiled_module,
-                arg_inputs=torch_inputs,
-                kwarg_inputs=torch_kwarg_inputs,
-            )
         if outputs_match:
             logger.info("Refitting Succeed!")
         else: