diff --git a/tests/models/test_deepseek_v41_decoder_replay_layers.py b/tests/models/test_deepseek_v41_decoder_replay_layers.py
index 614d903ca1..b7f5ca29ec 100644
--- a/tests/models/test_deepseek_v41_decoder_replay_layers.py
+++ b/tests/models/test_deepseek_v41_decoder_replay_layers.py
@@ -8,6 +8,7 @@ import pytest
 import torch
 
 from vllm.config import CompilationConfig, CUDAGraphMode
+from vllm.config.kernel import FLASHINFER_MOE_EP_BACKENDS, NATIVE_MEGA_MOE_BACKENDS
 from vllm.forward_context import (
     BatchDescriptor,
     ForwardContext,
@@ -144,8 +145,18 @@ def test_piecewise_graphs_break_out_by_size():
     write_batch_kv.assert_called_once_with(*states)
 
 
-def test_replay_graph_matches_eager(monkeypatch):
-    """The replay graph of the next captured size pads and runs the rows."""
+@pytest.mark.parametrize(
+    ("moe_backend", "ids_dtype"),
+    [
+        ("auto", torch.int32),
+        *((b, torch.int64) for b in sorted(NATIVE_MEGA_MOE_BACKENDS)),
+        *((b, torch.int32) for b in sorted(FLASHINFER_MOE_EP_BACKENDS)),
+    ],
+    ids=str,
+)
+def test_replay_graph_matches_eager(monkeypatch, moe_backend, ids_dtype):
+    """The replay graph of the next captured size pads and runs the rows. Input ids
+    arrive as the model passes them: int32, cast to int64 for native MegaMoE only."""
     monkeypatch.setattr(cudagraph_utils, "get_pp_group", MagicMock)
     capture = torch.cuda.stream(torch.cuda.Stream())
     monkeypatch.setattr(cudagraph_utils, "graph_capture", lambda device: capture)
@@ -157,6 +168,7 @@ def test_replay_graph_matches_eager(monkeypatch):
     cfg.cache_config.use_kda_recoverssm = False
     cfg.model_config.hf_config = MagicMock(hc_mult=HC, hidden_size=HIDDEN)
     cfg.model_config.dtype = torch.float32
+    cfg.kernel_config.moe_backend = moe_backend
 
     def run_layers(hidden, positions, ids, pre, post, mix, residual):
         return residual + hidden[:, None] + positions[:, None, None], pre + ids[:, None]
@@ -173,6 +185,7 @@ def test_replay_graph_matches_eager(monkeypatch):
         torch.randn(12, *b.shape[1:], device=DEVICE).to(b.dtype)
         for b in manager.input_buffers
     ]
+    states[2] = torch.arange(12, device=DEVICE, dtype=ids_dtype)  # input_ids
     rows = torch.tensor([11, 2, 7], device=DEVICE)
     desc = manager.dispatch(2, 3, None, 0)
     with override_forward_context(_graph_context(desc.num_tokens)):
diff --git a/vllm/models/deepseek_v41/nvidia/decoder_replay_cudagraph.py b/vllm/models/deepseek_v41/nvidia/decoder_replay_cudagraph.py
index 871f535584..c985f973bb 100644
--- a/vllm/models/deepseek_v41/nvidia/decoder_replay_cudagraph.py
+++ b/vllm/models/deepseek_v41/nvidia/decoder_replay_cudagraph.py
@@ -10,7 +10,7 @@ import torch
 
 from vllm.compilation.breakable_cudagraph import BreakableCUDAGraphWrapper
 from vllm.config import CUDAGraphMode, VllmConfig
-from vllm.config.kernel import MEGA_MOE_BACKENDS
+from vllm.config.kernel import NATIVE_MEGA_MOE_BACKENDS
 from vllm.forward_context import get_forward_context, override_forward_context
 from vllm.models.deepseek_v41.decoder_replay_layers import DecoderReplayLayers
 from vllm.v1.worker.gpu.cudagraph_utils import (
@@ -56,8 +56,9 @@ class DecoderReplayCudaGraphManager(CudaGraphManager):
         config, act = vllm_config.model_config.hf_config, vllm_config.model_config.dtype
         assert isinstance(act, torch.dtype)
         hc, h, f32 = config.hc_mult, config.hidden_size, torch.float32
-        mega_moe = vllm_config.kernel_config.moe_backend in MEGA_MOE_BACKENDS
-        ids = torch.int64 if mega_moe else torch.int32
+        # DeepseekV4Model.forward casts input_ids to int64 for native MegaMoE only.
+        native = vllm_config.kernel_config.moe_backend in NATIVE_MEGA_MOE_BACKENDS
+        ids = torch.int64 if native else torch.int32
         # hidden_states, positions, input_ids, pre_mix, post_mix, res_mix, residual
         shapes = [(h,), (), (), (hc,), (hc, 1), (hc, hc), (hc, h)]
         dtypes = [act, torch.int64, ids, f32, f32, f32, act]