diff --git a/python/sglang/srt/managers/scheduler.py b/python/sglang/srt/managers/scheduler.py
index 79a8aa859..4df5b8a7e 100644
--- a/python/sglang/srt/managers/scheduler.py
+++ b/python/sglang/srt/managers/scheduler.py
@@ -1488,12 +1488,8 @@ class Scheduler(
         if self.device == "cpu":
             self.schedule_stream.synchronize = lambda: None  # No-op for CPU
         # The global WAR barrier fences the scheduler's next shared-buffer write
-        # on the forward's read-done event. DFLASH opts out: it fences its own
-        # req_to_token writes with verify_done / plan-stream deps, so the global
-        # barrier would only serialize plan overlap without adding correctness.
-        self._war_barrier_enabled = (
-            is_cuda() or envs.SGLANG_ENABLE_WAR_BARRIER.get()
-        ) and not self.spec_algorithm.is_dflash()
+        # on the previous forward's read of the shared pool.
+        self._war_barrier_enabled = is_cuda() or envs.SGLANG_ENABLE_WAR_BARRIER.get()
         with self.device_module.StreamContext(self.schedule_stream):
             dispatch_event_loop(self)
 
diff --git a/python/sglang/srt/speculative/dflash_info_v2.py b/python/sglang/srt/speculative/dflash_info_v2.py
index 36177b459..fa4d35942 100644
--- a/python/sglang/srt/speculative/dflash_info_v2.py
+++ b/python/sglang/srt/speculative/dflash_info_v2.py
@@ -46,7 +46,6 @@ class DFlashDraftInputV2(SpecInput):
     bonus_tokens: torch.Tensor
     new_seq_lens: torch.Tensor
     hidden_states: torch.Tensor
-    verify_done: Optional[torch.cuda.Event] = None
     max_top_k: int = 1
     uniform_top_k_value: Optional[int] = None
     reserved_seq_lens_cpu: Optional[torch.Tensor] = None
@@ -113,7 +112,6 @@ class DFlashDraftInputV2(SpecInput):
             bonus_tokens=torch.empty((0,), device=device, dtype=torch.int64),
             new_seq_lens=torch.empty((0,), device=device, dtype=torch.int64),
             hidden_states=torch.empty((0, 0), device=device, dtype=torch.float16),
-            verify_done=None,
         )
 
     def prepare_for_decode(self, batch: ScheduleBatch):
@@ -126,9 +124,6 @@ class DFlashDraftInputV2(SpecInput):
         the overallocated mapping.
         """
         plan_stream, plan_stream_ctx = _get_overlap_plan_stream(batch.device)
-        if plan_stream is None and self.verify_done is not None:
-            # Ensure previous forward is completed before mutating shared buffers.
-            self.verify_done.synchronize()
 
         bs = batch.batch_size()
         if bs == 0:
@@ -192,9 +187,6 @@ class DFlashDraftInputV2(SpecInput):
                 # The plan stream must wait for those writes before reading them.
                 plan_stream.wait_stream(caller_stream)
 
-            if plan_stream is not None and self.verify_done is not None:
-                plan_stream.wait_event(self.verify_done)
-
             cur_kv_lens = self._prepare_cur_kv_lens_gpu_buf[:bs]
             nxt_kv_lens = self._prepare_nxt_kv_lens_gpu_buf[:bs]
             cur_kv_lens.copy_(cur_kv_lens_cpu_t, non_blocking=True)
diff --git a/python/sglang/srt/speculative/dflash_worker_v2.py b/python/sglang/srt/speculative/dflash_worker_v2.py
index 94194665b..2553a2927 100644
--- a/python/sglang/srt/speculative/dflash_worker_v2.py
+++ b/python/sglang/srt/speculative/dflash_worker_v2.py
@@ -1233,7 +1233,6 @@ class DFlashWorkerV2(BaseSpecWorker):
         *,
         bonus_tokens: torch.Tensor,
         seq_lens: torch.Tensor,
-        verify_done: Optional[torch.cuda.Event] = None,
     ) -> DFlashDraftInputV2:
         bs = int(seq_lens.numel())
         device = bonus_tokens.device
@@ -1243,7 +1242,6 @@ class DFlashWorkerV2(BaseSpecWorker):
             bonus_tokens=bonus_tokens.to(dtype=torch.int64),
             new_seq_lens=seq_lens.to(dtype=torch.int64),
             hidden_states=torch.empty((bs, 0), device=device, dtype=torch.float16),
-            verify_done=verify_done,
         )
 
     def _make_next_draft_input_decode(
@@ -1251,7 +1249,6 @@ class DFlashWorkerV2(BaseSpecWorker):
         *,
         bonus_tokens: torch.Tensor,
         new_seq_lens: torch.Tensor,
-        verify_done: Optional[torch.cuda.Event] = None,
     ) -> DFlashDraftInputV2:
         bs = int(new_seq_lens.numel())
         device = bonus_tokens.device
@@ -1261,7 +1258,6 @@ class DFlashWorkerV2(BaseSpecWorker):
             bonus_tokens=bonus_tokens.to(dtype=torch.int64),
             new_seq_lens=new_seq_lens.to(dtype=torch.int64),
             hidden_states=torch.empty((bs, 0), device=device, dtype=torch.float16),
-            verify_done=verify_done,
         )
 
     def forward_batch_generation(
@@ -1331,9 +1327,6 @@ class DFlashWorkerV2(BaseSpecWorker):
                 bonus_tokens=next_token_ids,
                 seq_lens=batch.seq_lens,
             )
-            verify_done = torch.get_device_module(device).Event()
-            verify_done.record()
-            batch_output.next_draft_input.verify_done = verify_done
             return batch_output
 
         # Decode / target-verify stage.
@@ -1355,9 +1348,6 @@ class DFlashWorkerV2(BaseSpecWorker):
             )
             if on_publish is not None:
                 on_publish(next_draft_input.new_seq_lens)
-            verify_done = torch.get_device_module(self.device).Event()
-            verify_done.record()
-            next_draft_input.verify_done = verify_done
             return GenerationBatchResult(
                 logits_output=None,
                 next_token_ids=empty_ids,
@@ -1732,9 +1722,6 @@ class DFlashWorkerV2(BaseSpecWorker):
             bonus_tokens=bonus,
             new_seq_lens=new_seq_lens,
         )
-        verify_done = torch.get_device_module(device).Event()
-        verify_done.record()
-        next_draft_input.verify_done = verify_done
 
         return GenerationBatchResult(
             logits_output=logits_output,