diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index 8c0706539c..c4e18d9119 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -392,7 +392,9 @@ def index_dtype_validator(
 
 
 @dynamo_tensorrt_converter(
-    torch.ops.aten.index.Tensor, capability_validator=index_dtype_validator
+    torch.ops.aten.index.Tensor,
+    capability_validator=index_dtype_validator,
+    supports_dynamic_shapes=True,
 )
 @enforce_tensor_types(
     {
diff --git a/tests/py/dynamo/conversion/test_index_aten.py b/tests/py/dynamo/conversion/test_index_aten.py
index 8e21f945dc..fc4a70b1ff 100644
--- a/tests/py/dynamo/conversion/test_index_aten.py
+++ b/tests/py/dynamo/conversion/test_index_aten.py
@@ -168,7 +168,31 @@ def forward(self, input):
                 dtype=torch.float32,
             ),
         ]
-        self.run_test_with_dynamic_shape(TestModule(), input_specs)
+        self.run_test_with_dynamic_shape(
+            TestModule(), input_specs, use_dynamo_tracer=True
+        )
+
+
+class TestIndexDynamicInputNonDynamicIndexConverter(DispatchTestCase):
+    def test_index_input_non_dynamic_index_dynamic(self):
+        class TestIndexWithRuntimeIndex(torch.nn.Module):
+            def forward(self, x):
+                mask = x > 0
+                idx = torch.nonzero(mask, as_tuple=True)
+                return torch.ops.aten.index.Tensor(x, idx)
+
+        input_specs = [
+            Input(
+                min_shape=(2, 2),
+                opt_shape=(2, 2),
+                max_shape=(8, 8),
+                dtype=torch.float32,
+            ),
+        ]
+        # In this case the index args[1] gets itself converted to a List of TRTTensors with use_dynamo_tracer=True
+        self.run_test_with_dynamic_shape(
+            TestIndexWithRuntimeIndex(), input_specs, use_dynamo_tracer=True
+        )
 
 
 if __name__ == "__main__":