diff --git a/backends/cadence/aot/quantizer/fusion_pass.py b/backends/cadence/aot/quantizer/fusion_pass.py
index 7093ef19c3d..9c926d91000 100644
--- a/backends/cadence/aot/quantizer/fusion_pass.py
+++ b/backends/cadence/aot/quantizer/fusion_pass.py
@@ -432,12 +432,39 @@ def get_args_and_kwargs_mixed_w8a32_conv(
         torch.ops.aten.permute.default,
         (other_inputs[0], [0, 2, 1]),  # NCL -> NLC
     )
+    if "val" in other_inputs[0].meta:
+        original_val = other_inputs[0].meta["val"]
+        fake_mode = original_val.fake_mode
+        if fake_mode is not None:
+            with fake_mode:
+                transposed_inputs.meta["val"] = torch.ops.aten.permute.default(
+                    original_val, [0, 2, 1]
+                )
+        else:
+            shape = list(original_val.shape)
+            # NCL -> NLC: [0,1,2] -> [0,2,1]
+            shape[1], shape[2] = shape[2], shape[1]
+            transposed_inputs.meta["val"] = torch.zeros(shape, dtype=original_val.dtype)
     copy_node_metadata(transposed_inputs, other_inputs[0])
 
     transposed_weights = graph_module.graph.call_function(
         torch.ops.aten.permute.default,
         (weights_inputs[0], [2, 0, 1]),  # NCL -> LNC
     )
+    if "val" in weights_inputs[0].meta:
+        original_val = weights_inputs[0].meta["val"]
+        fake_mode = original_val.fake_mode
+        if fake_mode is not None:
+            with fake_mode:
+                transposed_weights.meta["val"] = torch.ops.aten.permute.default(
+                    original_val, [2, 0, 1]
+                )
+        else:
+            shape = list(original_val.shape)
+            # NCL -> LNC: [0,1,2] -> [2,0,1]
+            transposed_weights.meta["val"] = torch.zeros(
+                [shape[2], shape[0], shape[1]], dtype=original_val.dtype
+            )
     copy_node_metadata(transposed_weights, weights_inputs[0])
 
     args = (