Your current environment

Collecting environment information...

    System Info

============================== OS : Debian GNU/Linux 13 (trixie) (x86_64) GCC version : (Debian 14.2.0-19) 14.2.0 Clang version : Could not collect CMake version : version 3.31.6 Libc version : glibc-2.41

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

PyTorch version : 2.10.0+cu130 Is debug build : False CUDA used to build PyTorch : 13.0 ROCM used to build PyTorch : N/A

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

Python version : 3.13.5 (main, Jun 25 2025, 18:55:22) [GCC 14.2.0] (64-bit runtime) Python platform : Linux-6.12.74+deb13+1-amd64-x86_64-with-glibc2.41

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

Is CUDA available : True CUDA runtime version : 13.1.115 CUDA_MODULE_LOADING set to : GPU models and configuration : GPU 0: NVIDIA GeForce RTX 3090 GPU 1: NVIDIA GeForce RTX 3090 GPU 2: NVIDIA GeForce RTX 3090 GPU 3: NVIDIA GeForce RTX 3090

Nvidia driver version : 595.45.04 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 Address sizes: 48 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 32 On-line CPU(s) list: 0-31 Vendor ID: AuthenticAMD Model name: AMD Ryzen 9 7950X 16-Core Processor CPU family: 25 Model: 97 Thread(s) per core: 2 Core(s) per socket: 16 Socket(s): 1 Stepping: 2 Frequency boost: disabled CPU(s) scaling MHz: 43% CPU max MHz: 5881.0000 CPU min MHz: 545.0000 BogoMIPS: 8999.99 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 sse4_1 sse4_2 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 cat_l3 cdp_l3 hw_pstate ssbd mba perfmon_v2 ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase 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 avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic vgif x2avic v_spec_ctrl vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid overflow_recov succor smca fsrm flush_l1d amd_lbr_pmc_freeze Virtualization: AMD-V L1d cache: 512 KiB (16 instances) L1i cache: 512 KiB (16 instances) L2 cache: 16 MiB (16 instances) L3 cache: 64 MiB (2 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-31 Vulnerability Gather data sampling: 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 Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Mitigation; Safe RET 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: Mitigation; Clear CPU buffers Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

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

[pip3] flashinfer-python==0.6.7 [pip3] numpy==2.4.4 [pip3] nvidia-cublas==13.1.0.3 [pip3] nvidia-cuda-cupti==13.0.85 [pip3] nvidia-cuda-nvrtc==13.0.88 [pip3] nvidia-cuda-runtime==13.0.96 [pip3] nvidia-cudnn-cu13==9.15.1.9 [pip3] nvidia-cudnn-frontend==1.18.0 [pip3] nvidia-cufft==12.0.0.61 [pip3] nvidia-cufile==1.15.1.6 [pip3] nvidia-curand==10.4.0.35 [pip3] nvidia-cusolver==12.0.4.66 [pip3] nvidia-cusparse==12.6.3.3 [pip3] nvidia-cusparselt-cu13==0.8.0 [pip3] nvidia-cutlass-dsl==4.4.2 [pip3] nvidia-cutlass-dsl-libs-base==4.4.2 [pip3] nvidia-ml-py==13.595.45 [pip3] nvidia-nccl-cu13==2.28.9 [pip3] nvidia-nvjitlink==13.0.88 [pip3] nvidia-nvshmem-cu13==3.4.5 [pip3] nvidia-nvtx==13.0.85 [pip3] pyzmq==27.1.0 [pip3] torch==2.10.0+cu130 [pip3] torch_c_dlpack_ext==0.1.5 [pip3] torchaudio==2.10.0+cu130 [pip3] torchvision==0.25.0+cu130 [pip3] transformers==5.5.0 [pip3] triton==3.6.0 [conda] Could not collect

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

ROCM Version : Could not collect vLLM Version : 0.19.1rc1.dev40+g4dd49b06f (git sha: 4dd49b06f) vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X PHB PHB PHB 0-31 0 N/A GPU1 PHB X PHB PHB 0-31 0 N/A GPU2 PHB PHB X PHB 0-31 0 N/A GPU3 PHB PHB PHB X 0-31 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

LD_LIBRARY_PATH=/usr/local/cuda-13.1/lib64 PYTORCH_NVML_BASED_CUDA_CHECK=1 TORCHINDUCTOR_COMPILE_THREADS=1 TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_llm

🐛 Describe the bug

When using the below configuration with 4x3090 with VLLM nightly and CUDA130 the following happens:

vllm serve /nvme/llm/weight/gemma-4-31B-it \
  --tensor-parallel-size 4 \
  --max-model-len 131072 \
  --gpu-memory-utilization 0.88 \
  --enable-auto-tool-choice \
  --reasoning-parser gemma4 \
  --tool-call-parser gemma4 \
  --async-scheduling \
  --host 10.0.0.50 \
  --port 5000 \
  --api-key woot \
  --enable-prefix-caching \
  --mm-processor-kwargs '{"max_soft_tokens": 1120}' \
  --quantization "fp8"

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