diff --git a/onnxruntime/core/providers/shared/utils/utils.cc b/onnxruntime/core/providers/shared/utils/utils.cc
index 0eff00a532..7919f08166 100644
--- a/onnxruntime/core/providers/shared/utils/utils.cc
+++ b/onnxruntime/core/providers/shared/utils/utils.cc
@@ -32,38 +32,53 @@ bool GetClipMinMax(const InitializedTensorSet& initializers, const Node& node,
   if (!GetType(*node.InputDefs()[0], input_type, logger))
     return false;
 
-  if (input_type != ONNX_NAMESPACE::TensorProto_DataType_FLOAT) {
-    LOGS(logger, VERBOSE) << "GetClipMinMax() only support Clip node with float inputs for now. "
-                          << "The node [" << node_name << "] has input 0 type: " << input_type;
-    return false;
-  }
-
   min = std::numeric_limits<float>::lowest();
   max = std::numeric_limits<float>::max();
 
   if (node.SinceVersion() < 11) {  // Clip opset 1, 6 is using attributes for min/max
     NodeAttrHelper helper(node);
+    // attributes will be always float
     min = helper.Get("min", std::numeric_limits<float>::lowest());
     max = helper.Get("max", std::numeric_limits<float>::max());
   } else {
-    if (node.InputDefs().size() > 1) {  // we have input min
+    if (node.InputDefs().size() > 1) {
+      // we have input min
       const auto& min_name = node.InputDefs()[1]->Name();
       if (!Contains(initializers, min_name)) {
         LOGS(logger, VERBOSE) << "Input min of Clip must be known";
         return false;
       }
-      Initializer unpacked_tensor(*initializers.at(min_name));
-      min = unpacked_tensor.DataAsSpan<float>()[0];
-    }
-
-    if (node.InputDefs().size() > 2) {  // we have input max
-      const auto& max_name = node.InputDefs()[2]->Name();
-      if (!Contains(initializers, max_name)) {
-        LOGS(logger, VERBOSE) << "Input max of Clip must be known";
-        return false;
+      Initializer unpacked_tensor_min(*initializers.at(min_name));
+      switch (input_type) {
+        case ONNX_NAMESPACE::TensorProto_DataType_FLOAT:
+          min = unpacked_tensor_min.DataAsSpan<float>()[0];
+          break;
+        case ONNX_NAMESPACE::TensorProto_DataType_FLOAT16:
+          min = (unpacked_tensor_min.DataAsSpan<MLFloat16>()[0]).ToFloat();
+          break;
+        default:
+          LOGS(logger, VERBOSE) << "GetClipMinMax() only support Clip node with float inputs for now. "
+                                << "The node [" << node_name << "] has input 0 type: " << input_type;
+          return false;
+      }
+
+      if (node.InputDefs().size() > 2) {
+        // we have input max
+        const auto& max_name = node.InputDefs()[2]->Name();
+        if (!Contains(initializers, max_name)) {
+          LOGS(logger, VERBOSE) << "Input max of Clip must be known";
+          return false;
+        }
+        Initializer unpacked_tensor_max(*initializers.at(max_name));
+        switch (input_type) {
+          case ONNX_NAMESPACE::TensorProto_DataType_FLOAT:
+            max = unpacked_tensor_max.DataAsSpan<float>()[0];
+            break;
+          case ONNX_NAMESPACE::TensorProto_DataType_FLOAT16:
+            max = (unpacked_tensor_max.DataAsSpan<MLFloat16>()[0]).ToFloat();
+            break;
+        }
       }
-      Initializer unpacked_tensor(*initializers.at(max_name));
-      max = unpacked_tensor.DataAsSpan<float>()[0];
     }
   }