[fix] Skip routed expert capture for draft model under spec v2 (#26980)

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

python/sglang/srt/model_executor/model_runner.py

@@ -192,6 +192,7 @@ from sglang.srt.state_capturer.indexer_topk import (
 )
 from sglang.srt.state_capturer.routed_experts import (
     RoutedExpertsCapturer,
+    disable_routed_experts_capture_for_draft,
     get_global_experts_capturer,
     set_global_experts_capturer,
 )
@@ -699,6 +700,11 @@ class ModelRunner(ModelRunnerKVCacheMixin):
         self.load_model()
         self._prepare_moe_topk()
 
+        # Must run before backend/graph init so no draft graph records a
+        # routed-experts capture-write kernel.
+        if self.is_draft_worker:
+            disable_routed_experts_capture_for_draft(self.model)
+
         # Load the expert backup client
         self.expert_backup_client = (
             ExpertBackupClient(self.server_args, self)
@@ -960,6 +966,12 @@ class ModelRunner(ModelRunnerKVCacheMixin):
         self.model_config.full_attention_layer_ids = full_attention_layer_ids
 
     def init_routed_experts_capturer(self):
+        if self.is_draft_worker:
+            # Capture is target-only. The draft worker runs in the same process
+            # as its target and inits after it, so installing a capturer here
+            # would overwrite the target's process-global one.
+            return
+
         if not self.server_args.disable_shared_experts_fusion and hasattr(
             self.model, "num_fused_shared_experts"
         ):
@@ -2960,7 +2972,10 @@ class ModelRunner(ModelRunnerKVCacheMixin):
         output.expert_distribution_metrics = recorder_outputs.get("metrics")
 
         no_copy_to_cpu = not self.server_args.disable_overlap_schedule
-        if (experts_capturer := get_global_experts_capturer()) is not None:
+        if (
+            not self.is_draft_worker
+            and (experts_capturer := get_global_experts_capturer()) is not None
+        ):
             output.routed_experts_output = experts_capturer.on_forward_end(
                 forward_batch=forward_batch,
                 can_run_graph=output.can_run_graph,