diff --git a/vllm/model_executor/layers/fused_moe/prepare_finalize/deepep_ht.py b/vllm/model_executor/layers/fused_moe/prepare_finalize/deepep_ht.py
index 63312557d..61777fd99 100644
--- a/vllm/model_executor/layers/fused_moe/prepare_finalize/deepep_ht.py
+++ b/vllm/model_executor/layers/fused_moe/prepare_finalize/deepep_ht.py
@@ -107,15 +107,17 @@ class DeepEPHTPrepareAndFinalize(mk.FusedMoEPrepareAndFinalizeModular):
     ) -> Callable:
         has_scales = token_scales is not None
 
+        # Capture a DeepEP event on the compute stream before yielding.
+        # This must happen before the yield so the event only covers this
+        # ubatch's compute work. If captured after, the compute stream tail
+        # may include the other ubatch's work, preventing overlap.
+        previous_event = dbo_get_previous_event(self.buffer.capture)
+
         # We yield before launching the dispatch kernel since the dispatch
         # kernel will block the CPU so we want to queue up all the compute
         # for the other ubatch before the dispatch kernel starts.
         dbo_yield_and_switch_from_compute_to_comm()
 
-        # capture a DeepEP event and pass it as previous_event so
-        # DeepEP honors the dependency internally.
-        previous_event = dbo_get_previous_event(self.buffer.capture)
-
         (
             num_tokens_per_rank,
             num_tokens_per_rdma_rank,
@@ -357,11 +359,11 @@ class DeepEPHTPrepareAndFinalize(mk.FusedMoEPrepareAndFinalizeModular):
                 topk_ids=topk_ids,
                 apply_router_weight_on_input=apply_router_weight_on_input,
             )
+        previous_event = dbo_get_previous_event(self.buffer.capture)
         dbo_yield_and_switch_from_compute_to_comm()
         assert fused_expert_output.dtype == torch.bfloat16, (
             f"Expected fused_expert_output bfloat16, got {fused_expert_output.dtype}"
         )
-        previous_event = dbo_get_previous_event(self.buffer.capture)
         combined_x, _, event = self.buffer.combine(
             # HT combine only supports BF16
             x=fused_expert_output,