diff --git a/test/registered/quant/test_fp8_gemm_sm120.py b/test/registered/quant/test_fp8_gemm_sm120.py
new file mode 100644
index 000000000..f695851de
--- /dev/null
+++ b/test/registered/quant/test_fp8_gemm_sm120.py
@@ -0,0 +1,86 @@
+import unittest
+from types import SimpleNamespace
+from urllib.parse import urlparse
+
+from sglang.srt.utils import get_device_sm, kill_process_tree
+from sglang.test.ci.ci_register import register_cuda_ci
+from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    popen_launch_server,
+    try_cached_model,
+)
+
+register_cuda_ci(est_time=120, suite="stage-b-test-small-1-gpu")
+
+PERTENSOR_MODEL_PATH = "nvidia/Llama-3.1-8B-Instruct-FP8"
+BLOCKWISE_MODEL_PATH = "Qwen/Qwen3-4B-Instruct-2507-FP8"
+
+
+class FP8GemmSM120Base:
+    model_path = None
+    backend = None
+    quantization = None
+
+    @classmethod
+    def setUpClass(cls):
+        if cls.backend is None:
+            raise NotImplementedError("Subclass must set 'backend' attribute")
+        cls.model = try_cached_model(cls.model_path)
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        other_args = [
+            "--trust-remote-code",
+            "--fp8-gemm-backend",
+            cls.backend,
+            "--disable-piecewise-cuda-graph",
+        ]
+        if cls.quantization:
+            other_args += ["--quantization", cls.quantization]
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=other_args,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        if hasattr(cls, "process"):
+            kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        parsed_url = urlparse(self.base_url)
+        args = SimpleNamespace(
+            num_shots=self.num_shots,
+            data_path=None,
+            num_questions=1319,
+            max_new_tokens=512,
+            parallel=200,
+            host=parsed_url.hostname,
+            port=parsed_url.port,
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(f"{metrics=}")
+        self.assertGreaterEqual(metrics["accuracy"], self.accuracy_threshold)
+
+
+@unittest.skipIf(get_device_sm() < 100, "Test requires CUDA SM 100 or higher")
+class TestFP8PerTensorGemmSM120Auto(FP8GemmSM120Base, unittest.TestCase):
+    model_path = PERTENSOR_MODEL_PATH
+    backend = "auto"
+    quantization = "modelopt_fp8"
+    num_shots = 5
+    accuracy_threshold = 0.73
+
+
+@unittest.skipIf(get_device_sm() < 100, "Test requires CUDA SM 100 or higher")
+class TestFP8BlockwiseGemmSM120Auto(FP8GemmSM120Base, unittest.TestCase):
+    model_path = BLOCKWISE_MODEL_PATH
+    backend = "auto"
+    num_shots = 8
+    accuracy_threshold = 0.87
+
+
+if __name__ == "__main__":
+    unittest.main()