diff --git a/tests/operators/test_cutlass_fp8_fp8_half_block_gemm_fused.py b/tests/operators/test_cutlass_fp8_fp8_half_block_gemm_fused.py
new file mode 100644
index 00000000000..40bde7d8e23
--- /dev/null
+++ b/tests/operators/test_cutlass_fp8_fp8_half_block_gemm_fused.py
@@ -0,0 +1,108 @@
+# 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 os
+import unittest
+
+import numpy as np
+import paddle
+
+from fastdeploy.model_executor.ops.gpu import cutlass_fp8_fp8_half_block_gemm_fused
+
+BLOCK_SIZE = 128
+
+paddle.seed(2025)
+np.random.seed(2025)
+
+
+class TestCutlassFp8Fp8HalfBlockGemmFused(unittest.TestCase):
+    """Tests for cutlass_fp8_fp8_half_block_gemm_fused (FP8 block-scaled GEMM)."""
+
+    def setUp(self):
+        paddle.set_device("gpu")
+        self.prop = paddle.device.cuda.get_device_properties()
+        self.sm_version = self.prop.major * 10 + self.prop.minor
+        # Auto-tune mode lets the kernel find a valid config for each MNK.
+        os.environ["FLAGS_use_cutlass_device_best_config_path"] = "tune"
+
+    def tearDown(self):
+        os.environ.pop("FLAGS_use_cutlass_device_best_config_path", None)
+
+    def _skip_if_not_sm90(self):
+        if self.sm_version < 90:
+            self.skipTest(f"Requires SM90+ (current: SM{self.sm_version})")
+
+    def _check_output(self, m, n, k, output_dtype="bfloat16"):
+        """Run block GEMM and verify against dequant-matmul reference."""
+        scale_k = (k + BLOCK_SIZE - 1) // BLOCK_SIZE
+        scale_n = (n + BLOCK_SIZE - 1) // BLOCK_SIZE
+
+        x_fp8 = paddle.rand([m, k], dtype="bfloat16").astype("float8_e4m3fn")
+        y_fp8 = paddle.rand([n, k], dtype="bfloat16").astype("float8_e4m3fn")
+        x_scale = paddle.rand([scale_k, m], dtype="float32") * 0.9 + 0.1
+        y_scale = paddle.rand([scale_n, scale_k], dtype="float32") * 0.9 + 0.1
+
+        # Dequantize: expand block scales, then matmul in fp32
+        x_s = paddle.repeat_interleave(x_scale, BLOCK_SIZE, axis=0)[:k, :].transpose([1, 0])
+        y_s = paddle.repeat_interleave(y_scale, BLOCK_SIZE, axis=0)[:n, :]
+        y_s = paddle.repeat_interleave(y_s, BLOCK_SIZE, axis=1)[:, :k]
+        ref = paddle.matmul(
+            x_fp8.astype("float32") * x_s.astype("float32"),
+            y_fp8.astype("float32") * y_s.astype("float32"),
+            transpose_y=True,
+        )
+        out_t = paddle.bfloat16 if output_dtype == "bfloat16" else paddle.float16
+        ref = ref.astype(out_t)
+
+        result = cutlass_fp8_fp8_half_block_gemm_fused(
+            x_fp8,
+            y_fp8,
+            x_scale,
+            y_scale,
+            None,
+            transpose_x=False,
+            transpose_y=True,
+            output_dtype=output_dtype,
+            act="",
+        )
+
+        self.assertEqual(result.shape, [m, n])
+        self.assertEqual(result.dtype, out_t)
+        np.testing.assert_allclose(
+            ref.astype("float32").numpy(),
+            result.astype("float32").numpy(),
+            rtol=5e-2,
+            atol=5e-2,
+        )
+
+    def test_bfloat16_correctness(self):
+        """BF16 output correctness with multiple shapes."""
+        self._skip_if_not_sm90()
+        for m, n, k in [(32, 2048, 2048), (64, 4096, 4096), (128, 5120, 5120)]:
+            with self.subTest(m=m, n=n, k=k):
+                self._check_output(m, n, k)
+
+    def test_float16_output(self):
+        """FP16 output correctness."""
+        self._skip_if_not_sm90()
+        self._check_output(64, 2048, 2048, output_dtype="float16")
+
+    def test_non_aligned_dimensions(self):
+        """N and K not aligned to block size 128."""
+        self._skip_if_not_sm90()
+        self._check_output(32, 2048, 5504)
+
+
+if __name__ == "__main__":
+    unittest.main()