diff --git a/onnxscript/optimizer/_constant_folding.py b/onnxscript/optimizer/_constant_folding.py
index 9a740c783..853436fce 100644
--- a/onnxscript/optimizer/_constant_folding.py
+++ b/onnxscript/optimizer/_constant_folding.py
@@ -974,6 +974,8 @@ def __init__(
         self._sizes: dict[str, int] = {}
         self._modified: bool = False
         self._state = OptimizerState()
+        # Count of unknown (None) symbolic dimensions seen so far for generating unique names
+        self._unknown_dim_count = 0
         self._reset()
 
     def _reset(self) -> None:
@@ -982,6 +984,7 @@ def _reset(self) -> None:
         self._sizes = {}
         self._modified = False
         self._state = OptimizerState()
+        self._unknown_dim_count = 0
 
     def _do_inference(self, node: ir.Node) -> None:
         output_types = {}
@@ -1029,7 +1032,15 @@ def get_type(value: ir.Value) -> onnx.TypeProto | None:
                         inferred_shape = ir.serde.deserialize_type_proto_for_shape(
                             inferred_type
                         )
-                        output.shape = _merge_shapes(output.shape, inferred_shape)
+                        merged_shape = _merge_shapes(output.shape, inferred_shape)
+
+                        # Replace unknown dims with uniquely named symbolic dims
+                        assert merged_shape is not None
+                        for i in range(len(merged_shape)):
+                            if merged_shape.is_unknown_dim(i):
+                                merged_shape[i] = ir.SymbolicDim(self._new_unknown_dim_name())
+
+                        output.shape = merged_shape
                         output.type = ir.serde.deserialize_type_proto_for_type(inferred_type)
             except Exception as e:
                 logger.debug(
@@ -1038,6 +1049,12 @@ def get_type(value: ir.Value) -> onnx.TypeProto | None:
                     e,
                 )
 
+    def _new_unknown_dim_name(self) -> str:
+        """Generate a new unique name for an unknown (None) symbolic dimension."""
+        name = f"unknown_{self._unknown_dim_count}"
+        self._unknown_dim_count += 1
+        return name
+
     def new_constant(self, node: ir.Node, value) -> ir.Node | None:
         irvalue = node.outputs[0]
         if not isinstance(value, np.ndarray):