diff --git a/examples/router_replay/README.md b/examples/router_replay/README.md
index c8c556b8f8b..93006431ee2 100644
--- a/examples/router_replay/README.md
+++ b/examples/router_replay/README.md
@@ -68,4 +68,4 @@ actor_rollout_ref.actor.router_replay.mode="R3"
 actor_rollout_ref.rollout.enable_rollout_routing_replay=True
 ```
 
-R3 mode requires the rollout backend to support returning router selection results. Currently, this functionality is being tested based on the vllm implementation at https://github.com/vllm-project/vllm/pull/28284 and SGLang implementation at https://github.com/sgl-project/sglang/commit/bed301a5acaa9577c9aa706468bdf242f6a43051.
+R3 mode requires the rollout backend to support returning router selection results. Currently, this functionality is being tested based on the vllm implementation at https://github.com/vllm-project/vllm/pull/28284 as well as bug fix at https://github.com/vllm-project/vllm/pull/33013 and SGLang implementation at https://github.com/sgl-project/sglang/commit/bed301a5acaa9577c9aa706468bdf242f6a43051.
diff --git a/examples/router_replay/run_qwen30_a3b_megatron_vllm.sh b/examples/router_replay/run_qwen30_a3b_megatron_vllm.sh
index 9a45bdaac73..74e7af0dee0 100644
--- a/examples/router_replay/run_qwen30_a3b_megatron_vllm.sh
+++ b/examples/router_replay/run_qwen30_a3b_megatron_vllm.sh
@@ -6,7 +6,9 @@ NODES=1
 # R2: enable routing replay
 # R3: enable rollout routing replay
 # If enabling R3, please set actor_rollout_ref.rollout.enable_rollout_routing_replay=True
-# R3 example is based on vllm related pr https://github.com/vllm-project/vllm/pull/5322
+# R3 example is based on vllm related pr:
+#   - https://github.com/vllm-project/vllm/pull/28284
+#   - https://github.com/vllm-project/vllm/pull/33013
 
 ROUTING_REPLAY_MODE="R2" 
 
diff --git a/verl/utils/megatron/router_replay_patch.py b/verl/utils/megatron/router_replay_patch.py
index 328b93f99dd..8311126043e 100644
--- a/verl/utils/megatron/router_replay_patch.py
+++ b/verl/utils/megatron/router_replay_patch.py
@@ -84,6 +84,7 @@ def __init__(self):
         self.recorded_topk_idx = None  # For recording
         self.router_replay_action = None  # Router replay action for this layer
         self.replay_backward_list = []  # List of tensors for backward pass replay
+        self.layer_number = None  # Global layer index if available
         RouterReplay.router_instances.append(self)
 
     def set_target_indices(self, topk_indices: torch.Tensor):
@@ -336,6 +337,12 @@ def patched_tf_config_init(self, *args, **kwargs):
         return
 
     original_init = TopKRouter.__init__
+    original_set_layer_number = TopKRouter.set_layer_number
+
+    def patched_set_layer_number(self, layer_number: int):
+        original_set_layer_number(self, layer_number)
+        if self.router_replay is not None:
+            self.router_replay.layer_number = layer_number
 
     # Step 3: Define the new __init__ method
     def patched_init(self, *args, **kwargs):
@@ -374,4 +381,5 @@ def patched_preprocess(self, routing_map):
     # Step 5: Apply the patches
     TopKRouter.__init__ = patched_init
     TopKRouter.routing = patched_routing
+    TopKRouter.set_layer_number = patched_set_layer_number
     TopKRouter._router_replay_patched = True
diff --git a/verl/utils/megatron/router_replay_utils.py b/verl/utils/megatron/router_replay_utils.py
index b1a42840377..b3774102c14 100644
--- a/verl/utils/megatron/router_replay_utils.py
+++ b/verl/utils/megatron/router_replay_utils.py
@@ -242,11 +242,24 @@ def set_router_replay_data(layers_topk_idx, attention_mask, tf_config, vp_rank=N
         layers_topk_idx_reshape = layers_topk_idx_rmpad_split.permute(0, 2, 1, 3).squeeze(
             dim=0
         )  # layer_num, dynamic_bs_all, topk
+        num_layers_in_data = layers_topk_idx_reshape.shape[0]
+        use_global_layer_index = getattr(tf_config, "num_layers", None) == num_layers_in_data
         local_rank_info = get_current_rank_layer_info(tf_config, vp_rank)
         offset, _ = local_rank_info["start"], local_rank_info["end"]
         router_instances_list = RouterReplayHelper.get_micro_batch_router_list(tf_config, vp_rank)
         for i, router in enumerate(router_instances_list):
-            router.set_target_indices(layers_topk_idx_reshape[i + offset].to(torch.int64))
+            layer_idx = None
+            if use_global_layer_index:
+                layer_number = getattr(router, "layer_number", None)
+                if layer_number is not None:
+                    layer_idx = layer_number - 1
+            if layer_idx is None:
+                layer_idx = i + offset
+            if layer_idx < 0 or layer_idx >= num_layers_in_data:
+                raise ValueError(
+                    f"router replay layer index {layer_idx} out of range for data with {num_layers_in_data} layers"
+                )
+            router.set_target_indices(layers_topk_idx_reshape[layer_idx].to(torch.int64))
 
 
 def reorder_and_merge_vpp_layers(