diff --git a/tests/onnx/test_auto_scan_sum_7.py b/tests/onnx/test_auto_scan_sum_7.py
new file mode 100644
index 0000000000000000000000000000000000000000..d9b28779658cb969f5680319a2292ac19531eec3
--- /dev/null
+++ b/tests/onnx/test_auto_scan_sum_7.py
@@ -0,0 +1,59 @@
+# Copyright (c) 2022  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import OPConvertAutoScanTest
+from hypothesis import reproduce_failure
+from onnxbase import randtool
+import hypothesis.strategies as st
+import numpy as np
+import unittest
+
+
+class TestSumConvert(OPConvertAutoScanTest):
+    """
+    ONNX op: Sum
+    OPset version: 7
+    """
+
+    def sample_convert_config(self, draw):
+        input1_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=10, max_value=20), min_size=2, max_size=4))
+
+        input_dtype = draw(st.sampled_from(["float32"]))
+
+        config = {
+            "op_names": ["Sum"],
+            "test_data_shapes": [input1_shape, input1_shape],
+            "test_data_types": [[input_dtype], [input_dtype]],
+            "inputs_shape": [],
+            "min_opset_version": 7,
+            "max_opset_version": 7,
+            "inputs_name": ["x", "y"],
+            "outputs_name": ["z"],
+            "delta": 1e-4,
+            "rtol": 1e-4
+        }
+
+        attrs = {}
+
+        return (config, attrs)
+
+    def test(self):
+        self.run_and_statis(max_examples=30)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/tests/onnx/test_auto_scan_sum_8.py b/tests/onnx/test_auto_scan_sum_8.py
new file mode 100644
index 0000000000000000000000000000000000000000..303ee27933a4cb3dbb61b42cbce4cac6a84e6382
--- /dev/null
+++ b/tests/onnx/test_auto_scan_sum_8.py
@@ -0,0 +1,67 @@
+# Copyright (c) 2022  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import OPConvertAutoScanTest
+from hypothesis import reproduce_failure
+from onnxbase import randtool
+import hypothesis.strategies as st
+import numpy as np
+import unittest
+
+
+class TestSumConvert(OPConvertAutoScanTest):
+    """
+    ONNX op: Sum
+    OPset version: 8~15
+    """
+
+    def sample_convert_config(self, draw):
+        input1_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=10, max_value=20), min_size=2, max_size=4))
+
+        if draw(st.booleans()):
+            input2_shape = [input1_shape[-1]]
+        else:
+            input2_shape = input1_shape
+
+        def generator_data():
+            input_data = randtool("float", -5.0, 5.0, input2_shape)
+            input_data[abs(input_data) < 1.0] = 1.0
+            return input_data
+
+        input_dtype = draw(st.sampled_from(["float32"]))
+        config = {
+            "op_names": ["Sum"],
+            "test_data_shapes": [input1_shape, generator_data],
+            "test_data_types": [[input_dtype], [input_dtype]],
+            "inputs_shape": [],
+            "min_opset_version": 8,
+            "inputs_name": ["x", "y"],
+            "outputs_name": ["z"],
+            "delta": 1e-4,
+            "rtol": 1e-4
+        }
+
+        attrs = {}
+
+        return (config, attrs)
+
+    def test(self):
+        self.run_and_statis(max_examples=30)
+
+
+if __name__ == "__main__":
+    unittest.main()