diff --git a/onnxruntime/python/tools/quantization/qdq_quantizer.py b/onnxruntime/python/tools/quantization/qdq_quantizer.py
index b0153aed766ad..123cfe913d6e2 100644
--- a/onnxruntime/python/tools/quantization/qdq_quantizer.py
+++ b/onnxruntime/python/tools/quantization/qdq_quantizer.py
@@ -270,6 +270,8 @@ def quantize_model(self):
 
         self.model.model.producer_name = __producer__
         self.model.model.producer_version = __version__
+        if self.qdq_op_domain == ms_domain:
+            self.model.set_opset_import(ms_domain, 1)
 
         return self.model.model
 
diff --git a/onnxruntime/test/python/quantization/test_qdq.py b/onnxruntime/test/python/quantization/test_qdq.py
index 4de797400836f..223f405e8947a 100644
--- a/onnxruntime/test/python/quantization/test_qdq.py
+++ b/onnxruntime/test/python/quantization/test_qdq.py
@@ -601,6 +601,13 @@ def verify_qdq(self, per_channel, activation_type, weight_type, extra_options=No
         )
         check_model_correctness(self, model_fp32_path, model_qdq_path, data_reader.get_next())
 
+        # If the model uses Q/DQ ops with "com.microsoft" domain (e.g., for int16 support),
+        # then ensure the model has the appropriate opset import.
+        if extra_options and extra_options.get("UseQDQContribOps", False):
+            qdq_model = onnx.load_model(model_qdq_path)
+            ms_opset = next((opset for opset in qdq_model.opset_import if opset.domain == "com.microsoft"), None)
+            self.assertIsNot(ms_opset, None)
+
     def verify_qop(self, per_channel, is_quant_type_int8):
         np.random.seed(1)
         model_fp32_path = str(Path(self._tmp_model_dir.name) / f"conv_relu_fp32.{per_channel}.onnx")