diff --git a/python/paddle/fluid/tests/unittests/test_static_save_load.py b/python/paddle/fluid/tests/unittests/test_static_save_load.py
index c47daba96847ab681b37133d51826dec781b2ce3..2a30088a001ffdd23443dd2c8b1cd2d4130da33f 100644
--- a/python/paddle/fluid/tests/unittests/test_static_save_load.py
+++ b/python/paddle/fluid/tests/unittests/test_static_save_load.py
@@ -1626,6 +1626,35 @@ class TestStaticSaveLoadPickle(unittest.TestCase):
                         np.testing.assert_array_equal(new_t, base_t)
 
 
+class TestSaveLoadInferenceModel(unittest.TestCase):
+
+    def setUp(self):
+        self.temp_dir = tempfile.TemporaryDirectory()
+        self.model_path = os.path.join(self.temp_dir.name, 'no_params')
+
+    def tearDown(self):
+        self.temp_dir.cleanup()
+
+    def test_no_params(self):
+        main_program = framework.Program()
+        with framework.program_guard(main_program):
+            x = paddle.static.data(name="x", shape=[10, 10], dtype='float32')
+            y = x + x
+
+            place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+
+            paddle.static.save_inference_model(self.model_path, [x], [y], exe)
+
+            [inference_program, feed_target_names, fetch_targets
+             ] = (paddle.static.load_inference_model(self.model_path, exe))
+
+            self.assertEqual(feed_target_names, ['x'])
+            self.assertEqual(fetch_targets[0].shape, (10, 10))
+            ops = [op.type for op in inference_program.block(0).ops]
+            self.assertEqual(ops, ['feed', 'elementwise_add', 'scale', 'fetch'])
+
+
 if __name__ == '__main__':
     paddle.enable_static()
     unittest.main()
diff --git a/python/paddle/static/io.py b/python/paddle/static/io.py
index f0019df696b9713908a1fde1156db88b0f24ad7e..de9e48b3367cc70ec6139e9dcdf6859d926db9e9 100644
--- a/python/paddle/static/io.py
+++ b/python/paddle/static/io.py
@@ -542,7 +542,9 @@ def save_inference_model(path_prefix, feed_vars, fetch_vars, executor,
     save_to_file(model_path, program_bytes)
     # serialize and save params
     params_bytes = _serialize_persistables(program, executor)
-    save_to_file(params_path, params_bytes)
+    # program may not contain any parameter and just compute operation
+    if params_bytes is not None:
+        save_to_file(params_path, params_bytes)
 
 
 @static_only
@@ -660,6 +662,12 @@ def deserialize_persistables(program, data, executor):
         check_vars.append(var)
         load_var_map[var_copy.name] = var_copy
 
+    if data is None:
+        assert len(
+            origin_shape_map
+        ) == 0, "Required 'data' shall be not None if program contains parameter, but received 'data' is None."
+        return
+
     # append load_combine op to load parameters,
     load_var_list = []
     for name in sorted(load_var_map.keys()):
@@ -849,7 +857,9 @@ def load_inference_model(path_prefix, executor, **kwargs):
         params_filename = os.path.basename(params_path)
         # load params data
         params_path = os.path.join(load_dirname, params_filename)
-        params_bytes = load_from_file(params_path)
+        params_bytes = None
+        if os.path.exists(params_path):
+            params_bytes = load_from_file(params_path)
 
     # deserialize bytes to program
     program = deserialize_program(program_bytes)