diff --git a/test/export/test_export.py b/test/export/test_export.py
index ba8ed0299c975a..d3800c3ff9ffb1 100644
--- a/test/export/test_export.py
+++ b/test/export/test_export.py
@@ -2870,6 +2870,25 @@ def forward(self, x):
         # this doesn't work today
         gm_unflat_strict = unflatten(ep)
 
+    def test_nonstrict_retrace_preserves_metadata(self):
+        class MyModule(torch.nn.Module):
+            def __init__(self):
+                super().__init__()
+                self.linear = torch.nn.Linear(4, 4)
+
+            def forward(self, x):
+                return self.linear(x)
+
+        inp = torch.randn(4, 4)
+        m = MyModule()
+        ep = torch.export.export(m, (inp,), {}, strict=False)
+        # retrace
+        ep2 = torch.export.export(ep.module(), (inp,), {}, strict=False)
+
+        for n1, n2 in zip(list(ep.graph.nodes), list(ep2.graph.nodes)):
+            self.assertEqual(n1.meta.get("stack_trace"), n2.meta.get("stack_trace"))
+
+
 @unittest.skipIf(not torchdynamo.is_dynamo_supported(), "dynamo isn't support")
 class TestOneOffModelExportResult(TestCase):
     def test_scaled_dot_product_attention_cpu(self):
diff --git a/torch/export/_trace.py b/torch/export/_trace.py
index 27977b7bd76bc8..7c035b118aa895 100644
--- a/torch/export/_trace.py
+++ b/torch/export/_trace.py
@@ -551,9 +551,14 @@ def __init__(self, mod):
 
                     def forward(self, *args, **kwargs):
                         nonlocal out_spec
-                        flat_outs, out_spec = pytree.tree_flatten(
-                            self._export_root(*args, **kwargs)
-                        )
+                        if isinstance(self._export_root, torch.fx.GraphModule):
+                            with torch.fx.traceback.preserve_node_meta():
+                                tree_out = torch.fx.Interpreter(self._export_root).run(
+                                    *args, **kwargs
+                                )
+                        else:
+                            tree_out = self._export_root(*args, **kwargs)
+                        flat_outs, out_spec = pytree.tree_flatten(tree_out)
                         return tuple(flat_outs)
 
                 wrapped_mod = Wrapper(mod)
@@ -581,8 +586,6 @@ def forward(self, *args, **kwargs):
                 for node in gm.graph.nodes:
                     if "nn_module_stack" in node.meta:
                         nn_module_stack = node.meta["nn_module_stack"]
-                        # Delete the wrapper module reference
-                        del nn_module_stack[""]
                         node.meta["nn_module_stack"] = {
                             fixup_key(key): val
                             for key, val in pytree.tree_map(