diff --git a/tests/operators/test_draft_model_postprocess.py b/tests/operators/test_draft_model_postprocess.py
new file mode 100644
index 0000000000..d7ae34a3bf
--- /dev/null
+++ b/tests/operators/test_draft_model_postprocess.py
@@ -0,0 +1,84 @@
+# Copyright (c) 2025 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.
+import unittest
+
+import numpy as np
+import paddle
+
+from fastdeploy.model_executor.ops.gpu import draft_model_postprocess
+
+
+def draft_model_postprocess_cpu(
+    base_model_draft_tokens,
+    base_model_seq_lens_encoder,
+    base_model_stop_flags,
+):
+    bsz = base_model_draft_tokens.shape[0]
+    base_model_draft_token_len = base_model_draft_tokens.shape[1]
+    base_model_seq_lens_this_time = paddle.ones((bsz), dtype=paddle.int32)
+    for tid in range(bsz):
+        if (not base_model_stop_flags[tid]) and (base_model_seq_lens_encoder[tid] == 0):
+            base_model_draft_tokens_now = base_model_draft_tokens[tid]
+            token_num = 0
+            for i in range(base_model_draft_token_len):
+                if base_model_draft_tokens_now[i] != -1:
+                    token_num += 1
+
+            base_model_seq_lens_this_time[tid] = token_num
+        elif base_model_stop_flags[tid]:
+            base_model_seq_lens_this_time[tid] = 0
+
+    return base_model_seq_lens_this_time
+
+
+class TestDraftModelPostProcess(unittest.TestCase):
+    def _test_draft_model_postprocess(self, batch_size=1, base_model_draft_token_len=8192):
+        paddle.seed(66)
+        base_model_draft_tokens = paddle.randint(
+            low=-1,
+            high=1,
+            shape=[batch_size, base_model_draft_token_len],
+            dtype="int64",
+        )
+        base_model_seq_lens_encoder = paddle.randint(low=0, high=2, shape=[batch_size], dtype="int32")
+        random_floats = paddle.rand(shape=[batch_size])
+        base_model_stop_flags = random_floats >= 0.5
+
+        base_model_seq_lens_this_time = draft_model_postprocess_cpu(
+            base_model_draft_tokens,
+            base_model_seq_lens_encoder,
+            base_model_stop_flags,
+        )
+        base_model_seq_lens_this_time_gpu = paddle.ones((batch_size), dtype=paddle.int32)
+        draft_model_postprocess(
+            base_model_draft_tokens,
+            base_model_seq_lens_this_time_gpu,
+            base_model_seq_lens_encoder,
+            base_model_stop_flags,
+        )
+        np.testing.assert_allclose(base_model_seq_lens_this_time.numpy(), base_model_seq_lens_this_time_gpu.numpy())
+
+    def test_enough_cases(self):
+        self._test_draft_model_postprocess(100, 1024)
+        self._test_draft_model_postprocess(1, 11)
+        self._test_draft_model_postprocess(1, 8192)
+        self._test_draft_model_postprocess(2, 2048)
+        self._test_draft_model_postprocess(3, 1023)
+        self._test_draft_model_postprocess(4, 2047)
+        self._test_draft_model_postprocess(5, 4095)
+        self._test_draft_model_postprocess(10, 9191)
+
+
+if __name__ == "__main__":
+    unittest.main()