[Bug]: Qwen3 MoE GPTQ `qzeros` shape mismatch on ROCm gfx1201

[MartyMcFlyInTheSky]

Your current environment

Details

(Run from within remote container that I started via docker --context from host)

==============================
System Info

OS : Ubuntu 22.04.5 LTS (x86_64)
GCC version : (Ubuntu 11.4.0-1ubuntu1~22.04.3) 11.4.0
Clang version : 22.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-7.2.3 26084 f58b06dce1f9c15707c5f808fd002e18c2accf7e)
CMake version : version 3.31.10
Libc version : glibc-2.35

==============================
PyTorch Info

PyTorch version : 2.12.0+git6bbd260
Is debug build : False
CUDA used to build PyTorch : N/A
ROCM used to build PyTorch : 7.2.53211
XPU used to build PyTorch : N/A

==============================
Python Environment

Python version : 3.12.13 (main, Mar 4 2026, 09:23:07) [GCC 11.4.0] (64-bit runtime)
Python platform : Linux-7.0.0-28-generic-x86_64-with-glibc2.35

==============================
CUDA / GPU Info

Is CUDA available : True
CUDA runtime version : Could not collect
CUDA_MODULE_LOADING set to :
GPU models and configuration : (gfx1201)
Nvidia driver version : Could not collect
cuDNN version : Could not collect
HIP runtime version : 7.2.53211
MIOpen runtime version : 3.5.1
Is XNNPACK available : True

==============================
CPU Info

Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 192
On-line CPU(s) list: 0-191
Vendor ID: AuthenticAMD
Model name: AMD Ryzen Threadripper PRO 9995WX 96-Cores
CPU family: 26
Model: 8
Thread(s) per core: 2
Core(s) per socket: 96
Socket(s): 1
Stepping: 1
Frequency boost: enabled
CPU max MHz: 5460.5269
CPU min MHz: 1217.1060
BogoMIPS: 4992.72
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good amd_lbr_v2 nopl xtopology nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpuid_fault cpb cat_l3 cdp_l3 hw_pstate ssbd mba perfmon_v2 ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local user_shstk avx_vnni avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif x2avic v_spec_ctrl vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect movdiri movdir64b overflow_recov succor smca fsrm avx512_vp2intersect flush_l1d debug_swap amd_lbr_pmc_freeze
Virtualization: AMD-V
L1d cache: 4.5 MiB (96 instances)
L1i cache: 3 MiB (96 instances)
L2 cache: 96 MiB (96 instances)
L3 cache: 384 MiB (12 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-191
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: 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 Old microcode: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Mitigation; Reduced Speculation
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP always-on; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries

[pip3] conch-triton-kernels==1.2.1
[pip3] numpy==2.3.5
[pip3] onnx==1.22.0
[pip3] onnx-ir==0.2.1
[pip3] onnxscript==0.7.1
[pip3] onnxslim==0.1.95
[pip3] pyzmq==27.1.0
[pip3] torch==2.12.0+git6bbd260
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0+34c52a6
[pip3] torchvision==0.27.1+df56172
[pip3] transformers==5.14.1
[pip3] triton==3.7.1+git0263a6a6
[conda] Could not collect

==============================
vLLM Info

ROCM Version : 7.2.53211-c2d9476115
vLLM Version : 0.26.1rc1.dev542+gb22afe45a (git sha: b22afe4)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
============================ ROCm System Management Interface ============================
================================ Weight between two GPUs =================================
GPU0
GPU0 0

================================= Hops between two GPUs ==================================
GPU0
GPU0 0

=============================== Link Type between two GPUs ===============================
GPU0
GPU0 0

======================================= Numa Nodes =======================================
GPU[0] : (Topology) Numa Node: 0
GPU[0] : (Topology) Numa Affinity: -1
================================== End of ROCm SMI Log ===================================

==============================
Environment Variables

LD_LIBRARY_PATH=/opt/rocm/lib:/usr/local/lib:
PYTORCH_ROCM_ARCH=gfx90a;gfx942;gfx950;gfx1100;gfx1101;gfx1200;gfx1201;gfx1150;gfx1151
MAX_JOBS=16
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_root

🐛 Describe the bug

Qwen/Qwen3-30B-A3B-GPTQ-Int4 cannot start on ROCm. vLLM reaches model warmup, then the RDNA W4A16 kernel rejects the GPTQ zero-point layout:

AssertionError: zp shape mismatch: torch.Size([16, 640]) vs (5120, 16)

Is this checkpoint layout unsupported, or should the ROCm kernel transpose/normalize qzeros before the assertion?

Environment

• vLLM image: vllm/vllm-openai-rocm@sha256:8f71438ee82c2022cdca92ffc8e7d93573e65f3bf59c2d5d915a5ed7d13db1e2
• vLLM: 0.26.1rc1.dev542+gb22afe45
• Model: Qwen/Qwen3-30B-A3B-GPTQ-Int4 (revision=main)
• Quantization detected: auto_gptq
• GPU: AMD Radeon AI PRO R9700, gfx1201 (reported by host)
• Platform: ROCm Docker image, single GPU, tensor parallel size 1
• Context: 32768
• GPU memory utilization: 0.90

Reproduction

docker --context <remote-context> compose \
  -f compose.yaml up vllm

compose.yaml defines the elevant server arguments:

Qwen/Qwen3-30B-A3B-GPTQ-Int4
--max-model-len 32768
--gpu-memory-utilization 0.90
--reasoning-parser qwen3
--enable-auto-tool-choice
--tool-call-parser hermes
--default-chat-template-kwargs '{"enable_thinking":true}'

Relevant startup output:

Using RDNAHybridW4A16LinearKernel for AutoGPTQLinearMethod
Layer 'model.layers.0.mlp.experts' is not supported by GPTQMoeMarlin.
Falling back to Moe WNA16 kernels.
Using 'TRITON' WNA16 MoE backend.
Loading weights took 102.46 seconds
Model loading took 15.65 GiB memory

Failure:

File .../vllm/model_executor/kernels/linear/mixed_precision/rdna_hybrid_w4a16.py, line 228
  assert zp.shape == (N, num_groups), (
AssertionError: zp shape mismatch: torch.Size([16, 640]) vs (5120, 16)

The failure occurs during dummy warmup/KV-cache profiling, before the API becomes healthy.

Backend tests

All tests used the same pinned nightly image, model, and runtime configuration.

--moe-backend	Result
omitted / triton	Reaches warmup, then fails with zp shape mismatch: torch.Size([16, 640]) vs (5120, 16)
emulation	WNA16 MoE backend 'EMULATION' does not support the deployment configuration since the MoeWNA16 checkpoint layout is not supported.
triton_unfused	moe_backend='triton_unfused' is not supported for WNA16 MoE. Expected one of ['triton', 'marlin', 'humming', 'flashinfer_trtllm', 'emulation'].
marlin	WNA16 MoE backend 'MARLIN' does not support the deployment configuration since the MoeWNA16 checkpoint layout is not supported.
humming	WNA16 MoE backend 'HUMMING' does not support the deployment configuration since kernel does not support current device rocm.
flashinfer_trtllm	WNA16 MoE backend 'FLASHINFER_TRTLLM' does not support the deployment configuration since kernel does not support current device rocm.

Questions

1. Is Qwen3-30B-A3B-GPTQ-Int4 expected to be supported by ROCm AutoGPTQ/WNA16 kernels on gfx1201?
2. Is qzeros shape [16, 640] a known checkpoint-layout variant requiring a transpose to [5120, 16]?
3. Is there a patch, conversion command, or supported quantization format we should use?
4. If this is fixed upstream, which commit/tag contains the fix?

The same checkpoint starts loading and consumes approximately 15.65 GiB before the kernel assertion; this is not an OOM or model-download failure.

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[github-actions]

CC @hongxiayang @tjtanaa @vllmellm @giuseppegrossi for ROCm-related issue