[Bug]: DeepEP with Qwen3-Coder Fails #21603
Description
Your current environment
The output of python collect_env.py
Collecting environment information... [0/1849]
==============================
System Info
==============================
OS : Alibaba Cloud Linux release 3 (Soaring Falcon) (x86_64)
GCC version : (GCC) 10.2.1 20200825 (Alibaba 10.2.1-3 2.32)
Clang version : Could not collect
CMake version : version 4.0.3
Libc version : glibc-2.32
==============================
PyTorch Info
==============================
PyTorch version : 2.7.1+cu126
Is debug build : False
CUDA used to build PyTorch : 12.6
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.11.0 (main, Mar 1 2023, 18:26:19) [GCC 11.2.0] (64-bit runtime)
Python platform : Linux-5.10.134-16.3.al8.x86_64-x86_64-with-glibc2.32
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : 12.8.61
CUDA_MODULE_LOADING set to : LAZY
GPU models and configuration :
GPU 0: NVIDIA H20-3e
GPU 1: NVIDIA H20-3e
GPU 2: NVIDIA H20-3e
GPU 3: NVIDIA H20-3e
GPU 4: NVIDIA H20-3e
GPU 5: NVIDIA H20-3e
GPU 6: NVIDIA H20-3e
GPU 7: NVIDIA H20-3e
Nvidia driver version : 570.133.20
cuDNN version : Could not collect
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 192
On-line CPU(s) list: 0-191
Thread(s) per core: 2
Core(s) per socket: 48
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
BIOS Vendor ID: Intel(R) Corporation
CPU family: 6
Model: 207
Model name: INTEL(R) XEON(R) PLATINUM 8575C
BIOS Model name: INTEL(R) XEON(R) PLATINUM 8575C
Stepping: 2
CPU MHz: 3193.877
CPU max MHz: 4000.0000
CPU min MHz: 800.0000
BogoMIPS: 5600.00
Virtualization: VT-x
L1d cache: 48K
L1i cache: 32K
L2 cache: 2048K
L3 cache: 327680K
NUMA node0 CPU(s): 0-47,96-143
NUMA node1 CPU(s): 48-95,144-191
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 invpcid_single cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm uintr md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
==============================
Versions of relevant libraries
==============================
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.6.4.1
[pip3] nvidia-cuda-cupti-cu12==12.6.80
[pip3] nvidia-cuda-nvrtc-cu12==12.6.77
[pip3] nvidia-cuda-runtime-cu12==12.6.77
[pip3] nvidia-cudnn-cu12==9.5.1.17
[pip3] nvidia-cufft-cu12==11.3.0.4
[pip3] nvidia-cufile-cu12==1.11.1.6
[pip3] nvidia-curand-cu12==10.3.7.77
[pip3] nvidia-cusolver-cu12==11.7.1.2
[pip3] nvidia-cusparse-cu12==12.5.4.2
[pip3] nvidia-cusparselt-cu12==0.6.3
[pip3] nvidia-nccl-cu12==2.26.2
[pip3] nvidia-nvjitlink-cu12==12.6.85
[pip3] nvidia-nvtx-cu12==12.6.77
[pip3] pyzmq==27.0.0
[pip3] torch==2.7.1
[pip3] torchaudio==2.7.1
[pip3] torchvision==0.22.1
[pip3] transformers==4.54.0.dev0
[pip3] triton==3.3.1
[conda] numpy 2.2.6 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.6.4.1 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.6.80 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.6.77 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.6.77 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.5.1.17 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.3.0.4 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.7.77 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.7.1.2 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.5.4.2 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.6.3 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.26.2 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.6.85 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.6.77 pypi_0 pypi
[conda] pyzmq 27.0.0 pypi_0 pypi
[conda] torch 2.7.1 pypi_0 pypi
[conda] torchaudio 2.7.1 pypi_0 pypi
[conda] torchvision 0.22.1 pypi_0 pypi
[conda] transformers 4.54.0.dev0 pypi_0 pypi
[conda] triton 3.3.1 pypi_0 pypi
==============================
vLLM Info
==============================
ROCM Version : Could not collect
Neuron SDK Version : N/A
vLLM Version : 0.10.1.dev34+g9c8b2c2a8 (git sha: 9c8b2c2a8)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
^[[4mGPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 CPU Affinity NUMA Affinity GPU NUMA ID^[[0m
GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 PIX NODE SYS SYS 0-47,96-143 0 N/A
GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 NODE PIX SYS SYS 0-47,96-143 0 N/A
GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 SYS SYS PIX NODE 48-95,144-191 1 N/A
GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 SYS SYS NODE NODE 48-95,144-191 1 N/A
GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 SYS SYS NODE PIX 48-95,144-191 1 N/A
GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X SYS SYS NODE NODE 48-95,144-191 1 N/A
NIC0 NODE PIX NODE NODE SYS SYS SYS SYS X NODE SYS SYS
NIC1 NODE NODE NODE PIX SYS SYS SYS SYS NODE X SYS SYS
NIC2 SYS SYS SYS SYS PIX NODE NODE NODE SYS SYS X NODE
NIC3 SYS SYS SYS SYS NODE NODE PIX NODE SYS SYS NODE X
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
NIC Legend:
NIC0: mlx5_bond_0
NIC1: mlx5_bond_1
NIC2: mlx5_bond_2
NIC3: mlx5_bond_3
==============================
Environment Variables
==============================
LD_LIBRARY_PATH=/usr/local/cuda/lib64:
NCCL_CUMEM_ENABLE=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY
🐛 Describe the bug
Reproduce Script
VLLM_ALL2ALL_BACKEND=deepep_low_latency VLLM_USE_DEEP_GEMM=1 vllm serve Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8 --disable-log-requests --tensor-parallel-size 1 --enable-expert-parallel --data-parallel-size 8Error Info
(EngineCore_2 pid=399817) File "/jeejee/miniconda3/envs/jeejee/lib/python3.11/site-packages/torch/_ops.py", line 756, in __call__ [69/1918]
(EngineCore_2 pid=399817) return self._op(*args, **kwargs)
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/layer.py", line 1594, in moe_forward
(EngineCore_2 pid=399817) return self.forward_impl(hidden_states, router_logits)
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/layer.py", line 1493, in forward_impl
(EngineCore_2 pid=399817) return self.forward_impl_chunked(hidden_states, router_logits)
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/layer.py", line 1476, in forward_impl_chunked
(EngineCore_2 pid=399817) process_chunk(chunk_start,
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/layer.py", line 1437, in process_chunk
(EngineCore_2 pid=399817) final_hidden_states = self.quant_method.apply(
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/quantization/fp8.py", line 1026, in apply
(EngineCore_2 pid=399817) return self.fused_experts(
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/miniconda3/envs/jeejee/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1751, in _wrapped_call_impl
(EngineCore_2 pid=399817) return self._call_impl(*args, **kwargs)
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/miniconda3/envs/jeejee/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1762, in _call_impl
(EngineCore_2 pid=399817) return forward_call(*args, **kwargs)
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/modular_kernel.py", line 741, in forward
(EngineCore_2 pid=399817) _expert_topk_weights) = self.prepare_finalize.prepare(
(EngineCore_2 pid=399817) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_2 pid=399817) File "/jeejee/Code/vllm/vllm/model_executor/layers/fused_moe/deepep_ll_prepare_finalize.py", line 125, in prepare
(EngineCore_2 pid=399817) assert hidden_size in self.SUPPORTED_HIDDEN_SIZES, \
(EngineCore_2 pid=399817) AssertionError: Hidden Size 6144 not in supported list of hidden sizes[2048, 2560, 4096, 5120, 7168]
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