[Bug]: Mismatched number of arguments

[jasl]

Your current environment

The output of python collect_env.py

cuDNN version                : Probably one of the following:
/usr/lib/aarch64-linux-gnu/libcudnn.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_adv.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_cnn.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_engines_precompiled.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_graph.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_heuristic.so.9.12.0
/usr/lib/aarch64-linux-gnu/libcudnn_ops.so.9.12.0
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         aarch64
CPU op-mode(s):                       64-bit
Byte Order:                           Little Endian
CPU(s):                               14
On-line CPU(s) list:                  0-13
Vendor ID:                            ARM
Model name:                           -
Model:                                0
Thread(s) per core:                   1
Core(s) per cluster:                  14
Socket(s):                            -
Cluster(s):                           1
Stepping:                             r0p0
CPU(s) scaling MHz:                   45%
CPU max MHz:                          2601.0000
CPU min MHz:                          54.0000
BogoMIPS:                             2000.00
Flags:                                fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt
L1d cache:                            896 KiB (14 instances)
L1i cache:                            896 KiB (14 instances)
L2 cache:                             14 MiB (14 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-13
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; __user pointer sanitization
Vulnerability Spectre v2:             Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
=============
[pip3] nvidia-cudnn-cu13==9.13.1.26
[pip3] nvidia-cudnn-frontend==1.14.1
[pip3] nvidia-cufft==12.0.0.15
[pip3] nvidia-cufile==1.15.0.42
[pip3] nvidia-curand==10.4.0.35
[pip3] nvidia-cusolver==12.0.3.29
[pip3] nvidia-cusparse==12.6.2.49
[pip3] nvidia-cusparselt-cu13==0.8.1
[pip3] nvidia-cutlass-dsl==4.2.1
[pip3] nvidia-ml-py==13.580.82
[pip3] nvidia-nccl-cu13==2.28.3
[pip3] nvidia-nvjitlink==13.0.39
[pip3] nvidia-nvshmem-cu13==3.4.5
[pip3] nvidia-nvtx==13.0.39
[pip3] pyzmq==27.1.0
[pip3] torch==2.9.0+cu130
[pip3] torchaudio==2.9.0
[pip3] torchvision==0.24.0
[pip3] transformers==4.56.2
[pip3] triton==3.5.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.1.dev10013+gf28cc5943.d20250929 (git sha: f28cc5943, date: 20250929)
vLLM Build Flags:
  CUDA Archs: 11.0a; ROCm: Disabled
GPU Topology:
        GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      0-13    0               N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

==============================
     Environment Variables
==============================
CUDAARCHS=110a
CUDA_ARCHITECTURES=110a
CUDA_ARCH_LIST=110a
MAX_JOBS=8
NVCC_THREADS=1
NVIDIA_DRIVER_CAPABILITIES=all
NVIDIA_VISIBLE_DEVICES=all
TORCH_CUDA_ARCH_LIST=11.0a
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1

🐛 Describe the bug

OMP_NUM_THREADS=8 VLLM_USE_AITER_UNIFIED_ATTENTION=1 VLLM_ATTENTION_BACKEND=FLASHINFER VLLM_USE_FLASHINFER_MOE_FP8=1 vllm serve --async-scheduling --gpu-memory-utilization 0.8 --enable-auto-tool-choice --tool-call-parser hermes --model=Qwen/Qwen3-30B-A3B-Instruct-2507

(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] WorkerProc hit an exception.
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] Traceback (most recent call last):
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 1132, in fast_plan_decode
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._plan_info = self._cached_module.plan(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]                       ^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "python/tvm_ffi/cython/function.pxi", line 678, in core.Function.__call__
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] TypeError: Mismatched number of arguments when calling: `plan(0: ffi.Tensor, 1: ffi.Tensor, 2: ffi.Tensor, 3: ffi.Tensor, 4: ffi.Tensor, 5: ffi.Tensor, 6: int, 7: int, 8: int, 9: int, 10: int, 11: bool, 12: int, 13: int, 14: bool, 15: int, 16: int, 17: bool) -> Array<int>`. Expected 18 but got 15 arguments
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] The above exception was the direct cause of the following exception:
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] Traceback (most recent call last):
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 666, in worker_busy_loop
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     output = func(*args, **kwargs)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]              ^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 344, in compile_or_warm_up_model
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     cuda_graph_memory_bytes = self.model_runner.capture_model()
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3526, in capture_model
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._capture_cudagraphs(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3593, in _capture_cudagraphs
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._dummy_run(num_tokens,
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     return func(*args, **kwargs)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]            ^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3149, in _dummy_run
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     .build_for_cudagraph_capture(common_attn_metadata)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/utils.py", line 307, in build_for_cudagraph_capture
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     return self.build(common_prefix_len=0,
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 654, in build
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     fast_plan_decode(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 1150, in fast_plan_decode
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     raise RuntimeError(f"Error in tensor core plan: {e}") from e
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] RuntimeError: Error in tensor core plan: Mismatched number of arguments when calling: `plan(0: ffi.Tensor, 1: ffi.Tensor, 2: ffi.Tensor, 3: ffi.Tensor, 4: ffi.Tensor, 5: ffi.Tensor, 6: int, 7: int, 8: int, 9: int, 10: int, 11: bool, 12: int, 13: int, 14: bool, 15: int, 16: int, 17: bool) -> Array<int>`. Expected 18 but got 15 arguments
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] Traceback (most recent call last):
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 1132, in fast_plan_decode
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._plan_info = self._cached_module.plan(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]                       ^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "python/tvm_ffi/cython/function.pxi", line 678, in core.Function.__call__
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] TypeError: Mismatched number of arguments when calling: `plan(0: ffi.Tensor, 1: ffi.Tensor, 2: ffi.Tensor, 3: ffi.Tensor, 4: ffi.Tensor, 5: ffi.Tensor, 6: int, 7: int, 8: int, 9: int, 10: int, 11: bool, 12: int, 13: int, 14: bool, 15: int, 16: int, 17: bool) -> Array<int>`. Expected 18 but got 15 arguments
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] The above exception was the direct cause of the following exception:
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] Traceback (most recent call last):
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 666, in worker_busy_loop
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     output = func(*args, **kwargs)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]              ^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 344, in compile_or_warm_up_model
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     cuda_graph_memory_bytes = self.model_runner.capture_model()
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3526, in capture_model
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._capture_cudagraphs(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3593, in _capture_cudagraphs
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     self._dummy_run(num_tokens,
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     return func(*args, **kwargs)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]            ^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3149, in _dummy_run
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     .build_for_cudagraph_capture(common_attn_metadata)
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/utils.py", line 307, in build_for_cudagraph_capture
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     return self.build(common_prefix_len=0,
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 654, in build
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     fast_plan_decode(
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]   File "/home/jasl/.venv/lib/python3.12/site-packages/vllm/v1/attention/backends/flashinfer.py", line 1150, in fast_plan_decode
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]     raise RuntimeError(f"Error in tensor core plan: {e}") from e
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671] RuntimeError: Error in tensor core plan: Mismatched number of arguments when calling: `plan(0: ffi.Tensor, 1: ffi.Tensor, 2: ffi.Tensor, 3: ffi.Tensor, 4: ffi.Tensor, 5: ffi.Tensor, 6: int, 7: int, 8: int, 9: int, 10: int, 11: bool, 12: int, 13: int, 14: bool, 15: int, 16: int, 17: bool) -> Array<int>`. Expected 18 but got 15 arguments
(Worker pid=2952) ERROR 09-30 13:16:20 [multiproc_executor.py:671]
(EngineCore_DP0 pid=2930) ERROR 09-30 13:16:20 [core.py:712] EngineCore failed to start.

Note: I'm wrong that I used a non-FP8 model, but the error is about Mismatched number of arguments, so I think it still valid

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[mhillebrand]

Upgrading to flashinfer-python==0.4.0 caused this problem for me. It went away when I downgraded to flashinfer-python==0.3.1.post1.

[jasl]

Upgrading to flashinfer-python==0.4.0 caused this problem for me. It went away when I downgraded to flashinfer-python==0.3.1.post1.

#26443
upgrades FI to 0.4.0, maybe CI can grab the issue, and dev could give a well fix

I can't downgrade to 0.3.1.x because I'm working on Jetson Thor

[mgoin]

Hi @jasl actually #26326 is technically what upgrades us to flashinfer 0.4.0 and implements the fix, my PR just enforces the package version by default. You should be able to pull latest main I see this issue fixed

[jasl]

Hi @jasl actually #26326 is technically what upgrades us to flashinfer 0.4.0 and implements the fix, my PR just enforces the package version by default. You should be able to pull latest main I see this issue fixed

Thank you for the work, I will try this weekend