diff --git a/python/sglang/srt/layers/sampler.py b/python/sglang/srt/layers/sampler.py
index b24bfc8da..73ef13c35 100644
--- a/python/sglang/srt/layers/sampler.py
+++ b/python/sglang/srt/layers/sampler.py
@@ -72,9 +72,11 @@ class Sampler(nn.Module):
                     # NOTE: the top_p_renorm_prob from flashinfer has numerical problems,
                     # https://github.com/flashinfer-ai/flashinfer/issues/708
                     # so we use the torch implementation.
+
+                    # clamp to avoid -inf
                     logprobs = torch.log(
                         top_p_normalize_probs_torch(probs, sampling_info.top_ps)
-                    )
+                    ).clamp(min=torch.finfo(probs.dtype).min)
 
                 max_top_k_round, batch_size = 32, probs.shape[0]
                 uniform_samples = torch.rand(
@@ -109,9 +111,10 @@ class Sampler(nn.Module):
                     sampling_info.need_min_p_sampling,
                 )
                 if return_logprob:
+                    # clamp to avoid -inf
                     logprobs = torch.log(
                         top_p_normalize_probs_torch(probs, sampling_info.top_ps)
-                    )
+                    ).clamp(min=torch.finfo(probs.dtype).min)
             else:
                 raise ValueError(
                     f"Invalid sampling backend: {global_server_args_dict['sampling_backend']}"
diff --git a/test/srt/sampling/penaltylib/test_srt_endpoint_with_penalizers.py b/test/srt/sampling/penaltylib/test_srt_endpoint_with_penalizers.py
index 34565c9ff..d9d77a9ae 100644
--- a/test/srt/sampling/penaltylib/test_srt_endpoint_with_penalizers.py
+++ b/test/srt/sampling/penaltylib/test_srt_endpoint_with_penalizers.py
@@ -36,7 +36,7 @@ class TestBatchPenalizerE2E(unittest.TestCase):
     def run_decode(
         self,
         return_logprob=True,
-        top_logprobs_num=3,
+        top_logprobs_num=5,
         return_text=True,
         n=1,
         **sampling_params,
@@ -58,8 +58,7 @@ class TestBatchPenalizerE2E(unittest.TestCase):
                 "logprob_start_len": 0,
             },
         )
-        print(json.dumps(response.json()))
-        print("=" * 100)
+        assert response.status_code == 200, "Request failed: " + response.text
 
     def test_default_values(self):
         self.run_decode()
@@ -112,4 +111,4 @@ class TestBatchPenalizerE2E(unittest.TestCase):
 
 
 if __name__ == "__main__":
-    unittest.main()
+    unittest.main(verbosity=3)