diff --git a/python/sglang/srt/managers/schedule_batch.py b/python/sglang/srt/managers/schedule_batch.py
index 205f31797..bd2158789 100644
--- a/python/sglang/srt/managers/schedule_batch.py
+++ b/python/sglang/srt/managers/schedule_batch.py
@@ -780,7 +780,7 @@ def top_k_top_p_sampling_from_probs_torch(
         sampled_index = torch.multinomial(probs_sort, num_samples=1)
     except RuntimeError:
         batch_next_token_ids = torch.zeros(
-            (probs_sort.shape[0],), dtype=torch.int64, device=probs.device
+            (probs_sort.shape[0],), dtype=torch.int32, device=probs.device
         )
         success = torch.zeros(probs.shape[0], dtype=torch.bool, device=probs.device)
         return batch_next_token_ids, success
diff --git a/python/sglang/srt/mem_cache/radix_cache.py b/python/sglang/srt/mem_cache/radix_cache.py
index c6fc3191b..347ae002e 100644
--- a/python/sglang/srt/mem_cache/radix_cache.py
+++ b/python/sglang/srt/mem_cache/radix_cache.py
@@ -74,7 +74,7 @@ class RadixCache(BasePrefixCache):
         if value:
             value = torch.concat(value)
         else:
-            value = torch.tensor([], dtype=torch.int64)
+            value = torch.tensor([], dtype=torch.int32)
         return value, last_node[0]
 
     def insert(self, key, value=None):
@@ -102,7 +102,7 @@ class RadixCache(BasePrefixCache):
             if del_in_memory_pool:
                 self.token_to_kv_pool.free(indices)
             else:
-                return torch.tensor([], dtype=torch.int64), self.root_node
+                return torch.tensor([], dtype=torch.int32), self.root_node
 
         # Radix Cache takes one ref in memory pool
         self.token_to_kv_pool.free(indices[last_uncached_pos:new_prefix_len])