diff --git a/onnxruntime/core/optimizer/insert_cast_transformer.cc b/onnxruntime/core/optimizer/insert_cast_transformer.cc
index 6c36f62015..41500af9c3 100644
--- a/onnxruntime/core/optimizer/insert_cast_transformer.cc
+++ b/onnxruntime/core/optimizer/insert_cast_transformer.cc
@@ -105,14 +105,22 @@ class RemoveDuplicateCastTransformer : public GraphTransformer {
       if (node.OpType() == "Cast") {
         // if cast's next node is also cast and next cast's output type equal to cast's input type
         // remove those two cast.
+        // boolean is an exception case for this optimization
         auto src_type = node.InputDefs()[0]->Type();
         auto dst_type = node.OutputDefs()[0]->Type();
+        if (*src_type == "tensor(bool)" || *dst_type == "tensor(bool)") return Status::OK();
         auto input = node.MutableInputDefs()[0];
         int child_removed = 0;
         int num_child = 0;
+        auto output_args = graph.GetOutputs();
+        std::unordered_set<const onnxruntime::NodeArg*> graph_outputs(output_args.begin(), output_args.end());
         for (auto it = node.OutputNodesBegin(); it != node.OutputNodesEnd(); ++it) {
           const Node& output_node{*it};
           if (output_node.OpType() == "Cast") {
+            // Skip if the node's output is also the output of the graph
+            if (graph_outputs.find(output_node.OutputDefs()[0]) != graph_outputs.end()) {
+              break;
+            }
             auto src_type1 = output_node.InputDefs()[0]->Type();
             auto dst_type1 = output_node.OutputDefs()[0]->Type();
             if (src_type == dst_type1 && src_type1 == dst_type) {