diff --git a/python/sglang/srt/model_executor/forward_batch_info.py b/python/sglang/srt/model_executor/forward_batch_info.py
index dd2b59728..d54b14ef2 100644
--- a/python/sglang/srt/model_executor/forward_batch_info.py
+++ b/python/sglang/srt/model_executor/forward_batch_info.py
@@ -148,9 +148,6 @@ class InputMetadata:
             self.extend_start_loc[1:] = torch.cumsum(self.extend_seq_lens[:-1], dim=0)
             self.extend_no_prefix = all(x == 0 for x in prefix_lens_cpu)
 
-    def init_total_num_tokens(self, batch: ScheduleBatch):
-        self.total_num_tokens = sum(len(req.fill_ids) for req in batch.reqs)
-
     @classmethod
     def from_schedule_batch(
         cls,
@@ -174,7 +171,11 @@ class InputMetadata:
 
         ret.compute_extend_infos(batch)
 
-        ret.init_total_num_tokens(batch)
+        if (
+            forward_mode != ForwardMode.DECODE
+            or model_runner.server_args.disable_flashinfer
+        ):
+            ret.total_num_tokens = int(torch.sum(ret.seq_lens))
 
         if forward_mode != ForwardMode.DECODE:
             ret.init_multimuldal_info(batch)
@@ -203,7 +204,7 @@ class InputMetadata:
 
     def init_triton_args(self, batch: ScheduleBatch, prefix_lens):
         """Init auxiliary variables for triton attention backend."""
-        self.triton_max_seq_len = max(len(r.fill_ids) for r in batch.reqs)
+        self.triton_max_seq_len = int(torch.max(self.seq_lens))
         self.triton_prefix_lens = prefix_lens
         self.triton_start_loc = torch.zeros_like(self.seq_lens, dtype=torch.int32)
         self.triton_start_loc[1:] = torch.cumsum(self.seq_lens[:-1], dim=0)