diff --git a/onnxruntime/core/providers/nuphar/scripts/symbolic_shape_infer.py b/onnxruntime/core/providers/nuphar/scripts/symbolic_shape_infer.py
index d834026f81..5ef2ac4c2a 100755
--- a/onnxruntime/core/providers/nuphar/scripts/symbolic_shape_infer.py
+++ b/onnxruntime/core/providers/nuphar/scripts/symbolic_shape_infer.py
@@ -903,7 +903,11 @@ class SymbolicShapeInference:
         scan_input_axes = get_attribute(node, 'scan_input_axes', [0]*num_scan_inputs)
         num_scan_states = len(node.input) - num_scan_inputs
         scan_input_axes = [handle_negative_axis(ax, self._get_shape_rank(node, i + num_scan_states)) for i, ax in enumerate(scan_input_axes)]
-        for i, si in enumerate(subgraph.input):
+        # We may have cases where the subgraph has optionial inputs that appear in both subgraph's input and initializer,
+        # but not in the node's input. In such cases, the input model might be invalid, but let's skip those optional inputs.
+        assert len(subgraph.input) >= len(node.input)
+        subgraph_inputs = subgraph.input[:len(node.input)]
+        for i, si in enumerate(subgraph_inputs):
             subgraph_name = si.name
             si.CopyFrom(self.known_vi_[node.input[i]])
             if i >= num_scan_states: