vllm - 💡(How to fix) Fix [Bug]: Garbled Output in DeepSeek-V4 with CUDA Graph Enabled Under Concurrent Identical Input Requests [1 participants]

Official PRs (…)
ON THIS PAGE

Recommended Tools

×6

Utilities matched from this issue’s tags and category — try them while you read without losing context.

GitHub issue graph ai analysis

Paste a GitHub issue URL. We fetch that issue, discover linked issues from bodies/comments/timeline, collect linked pull requests, and produce a structured English report.

The report is written in English Markdown for sharing and archival.

Helpful · Quick feedback

Loading…
GitHub stats
vllm-project/vllm#41331Fetched 2026-05-01 05:34:11
View on GitHub
Comments
0
Participants
1
Timeline
1
Reactions
3
Author
Participants
Timeline (top)
labeled ×1

Fix Action

Fix / Workaround

============================== 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): 256 On-line CPU(s) list: 0-255 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) 6767P CPU family: 6 Model: 173 Thread(s) per core: 2 Core(s) per socket: 64 Socket(s): 2 Stepping: 1 Frequency boost: enabled CPU max MHz: 2401.0000 CPU min MHz: 800.0000 BogoMIPS: 4800.00 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 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 avx2 smep bmi2 erms invpcid 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 avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 6 MiB (128 instances) L1i cache: 8 MiB (128 instances) L2 cache: 256 MiB (128 instances) L3 cache: 672 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-63,128-191 NUMA node1 CPU(s): 64-127,192-255 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 and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

Code Example

Collecting environment information...
==============================
        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                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.11.0+cu130
Is debug build               : False
CUDA used to build PyTorch   : 13.0
ROCM used to build PyTorch   : N/A
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-5.15.0-119-generic-x86_64-with-glibc2.35
    
==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 13.0.88
CUDA_MODULE_LOADING set to   : 
GPU models and configuration : 
GPU 0: NVIDIA B200
GPU 1: NVIDIA B200
GPU 2: NVIDIA B200
GPU 3: NVIDIA B200
GPU 4: NVIDIA B200
GPU 5: NVIDIA B200
GPU 6: NVIDIA B200
GPU 7: NVIDIA B200

Nvidia driver version        : 570.148.08
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:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               256
On-line CPU(s) list:                  0-255
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) 6767P
CPU family:                           6
Model:                                173
Thread(s) per core:                   2
Core(s) per socket:                   64
Socket(s):                            2
Stepping:                             1
Frequency boost:                      enabled
CPU max MHz:                          2401.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4800.00
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 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 avx2 smep bmi2 erms invpcid 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 avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            6 MiB (128 instances)
L1i cache:                            8 MiB (128 instances)
L2 cache:                             256 MiB (128 instances)
L3 cache:                             672 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-63,128-191
NUMA node1 CPU(s):                    64-127,192-255
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 and seccomp
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.8.post1
[pip3] numpy==2.2.6
[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==9.19.0.56
[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==2.11.0+cu130
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0+cu130
[pip3] torchvision==0.26.0+cu130
[pip3] transformers==5.6.2
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.20.1rc1.dev16+g7a1eb8ac2 (git sha: 7a1eb8ac2)
vLLM Build Flags:
  CUDA Archs: 7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX; ROCm: Disabled; XPU: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    NIC5    NIC6    NIC7    NIC8    NIC9    NIC10   CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV18    NV18    NV18    NV18    NV18    NV18    NV18    SYS     SYS     PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU1    NV18     X      NV18    NV18    NV18    NV18    NV18    NV18    SYS     SYS     NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU2    NV18    NV18     X      NV18    NV18    NV18    NV18    NV18    SYS     SYS     NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU3    NV18    NV18    NV18     X      NV18    NV18    NV18    NV18    SYS     SYS     NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU4    NV18    NV18    NV18    NV18     X      NV18    NV18    NV18    NODE    NODE    SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    SYS     64-127,192-255  1               N/A
GPU5    NV18    NV18    NV18    NV18    NV18     X      NV18    NV18    NODE    NODE    SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    SYS     64-127,192-255  1               N/A
GPU6    NV18    NV18    NV18    NV18    NV18    NV18     X      NV18    NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    SYS     64-127,192-255  1               N/A
GPU7    NV18    NV18    NV18    NV18    NV18    NV18    NV18     X      NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     SYS     64-127,192-255  1               N/A
NIC0    SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE     X      PIX     SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS
NIC1    SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    PIX      X      SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS
NIC2    PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS      X      NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE
NIC3    NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE     X      NODE    NODE    SYS     SYS     SYS     SYS     NODE
NIC4    NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE     X      NODE    SYS     SYS     SYS     SYS     NODE
NIC5    NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE    NODE     X      SYS     SYS     SYS     SYS     NODE
NIC6    SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS      X      NODE    NODE    NODE    SYS
NIC7    SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE     X      NODE    NODE    SYS
NIC8    SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE     X      NODE    SYS
NIC9    SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    NODE     X      SYS
NIC10   NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS      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_12
  NIC1: mlx5_13
  NIC2: mlx5_gdr_0
  NIC3: mlx5_gdr_1
  NIC4: mlx5_gdr_2
  NIC5: mlx5_gdr_3
  NIC6: mlx5_gdr_4
  NIC7: mlx5_gdr_5
  NIC8: mlx5_gdr_6
  NIC9: mlx5_gdr_7
  NIC10: mlx5_bond_0

==============================
     Environment Variables
==============================
NVIDIA_VISIBLE_DEVICES=all
NVIDIA_REQUIRE_CUDA=cuda>=13.0 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 brand=unknown,driver>=570,driver<571 brand=grid,driver>=570,driver<571 brand=tesla,driver>=570,driver<571 brand=nvidia,driver>=570,driver<571 brand=quadro,driver>=570,driver<571 brand=quadrortx,driver>=570,driver<571 brand=nvidiartx,driver>=570,driver<571 brand=vapps,driver>=570,driver<571 brand=vpc,driver>=570,driver<571 brand=vcs,driver>=570,driver<571 brand=vws,driver>=570,driver<571 brand=cloudgaming,driver>=570,driver<571 brand=unknown,driver>=575,driver<576 brand=grid,driver>=575,driver<576 brand=tesla,driver>=575,driver<576 brand=nvidia,driver>=575,driver<576 brand=quadro,driver>=575,driver<576 brand=quadrortx,driver>=575,driver<576 brand=nvidiartx,driver>=575,driver<576 brand=vapps,driver>=575,driver<576 brand=vpc,driver>=575,driver<576 brand=vcs,driver>=575,driver<576 brand=vws,driver>=575,driver<576 brand=cloudgaming,driver>=575,driver<576
TORCH_CUDA_ARCH_LIST=7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX
NVIDIA_DRIVER_CAPABILITIES=compute,utility
VLLM_USAGE_SOURCE=production-docker-image
CUDA_VERSION=13.0.2
VLLM_ENABLE_CUDA_COMPATIBILITY=0
VLLM_ENGINE_READY_TIMEOUT_S=3600
LD_LIBRARY_PATH=/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_root

---

IMAGE=vllm/vllm-openai:nightly

docker run -d \
  --gpus all \
  --name vllm-deepseek_v4 \
  -p 8000:8000 \
  --restart unless-stopped \
  -e VLLM_ENGINE_READY_TIMEOUT_S=3600 \
  -e VLLM_API_KEY=xxxx \
  -v $PROJ/models/deepseek-ai/DeepSeek-V4-Pro:/model \
  $IMAGE \
  --enable-prefix-caching \
  --enable-chunked-prefill \
  --model /model \
  --served-model-name inner-deepseek_v4 \
  --enable-expert-parallel \
  --tensor-parallel-size 8 \
  --host 0.0.0.0 \
  --port 8000 \
  --trust-remote-code \
  --gpu-memory-utilization 0.95 \
  --max-num-seqs 128 \
  --kv-cache-dtype fp8 \
  --block-size 256 \
  --compilation-config '{"mode":0,"cudagraph_mode":"FULL_DECODE_ONLY"}' \
  --attention_config.use_fp4_indexer_cache=True \
  --tokenizer-mode deepseek_v4 \
  --tool-call-parser deepseek_v4 \
  --enable-auto-tool-choice \
  --reasoning-parser deepseek_v4

---

Please give me the proof of Fermat's Little Theorem

---

for i in 1 2 3 4; do;  claude -p --output-format stream-json --verbose < prompt.txt > out-short-${i}.jsonl &; done; wait
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
Collecting environment information...
==============================
        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                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.11.0+cu130
Is debug build               : False
CUDA used to build PyTorch   : 13.0
ROCM used to build PyTorch   : N/A
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-5.15.0-119-generic-x86_64-with-glibc2.35
    
==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 13.0.88
CUDA_MODULE_LOADING set to   : 
GPU models and configuration : 
GPU 0: NVIDIA B200
GPU 1: NVIDIA B200
GPU 2: NVIDIA B200
GPU 3: NVIDIA B200
GPU 4: NVIDIA B200
GPU 5: NVIDIA B200
GPU 6: NVIDIA B200
GPU 7: NVIDIA B200

Nvidia driver version        : 570.148.08
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:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               256
On-line CPU(s) list:                  0-255
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) 6767P
CPU family:                           6
Model:                                173
Thread(s) per core:                   2
Core(s) per socket:                   64
Socket(s):                            2
Stepping:                             1
Frequency boost:                      enabled
CPU max MHz:                          2401.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4800.00
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 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 avx2 smep bmi2 erms invpcid 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 avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            6 MiB (128 instances)
L1i cache:                            8 MiB (128 instances)
L2 cache:                             256 MiB (128 instances)
L3 cache:                             672 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-63,128-191
NUMA node1 CPU(s):                    64-127,192-255
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 and seccomp
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.8.post1
[pip3] numpy==2.2.6
[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==9.19.0.56
[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==2.11.0+cu130
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.11.0+cu130
[pip3] torchvision==0.26.0+cu130
[pip3] transformers==5.6.2
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.20.1rc1.dev16+g7a1eb8ac2 (git sha: 7a1eb8ac2)
vLLM Build Flags:
  CUDA Archs: 7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX; ROCm: Disabled; XPU: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    NIC4    NIC5    NIC6    NIC7    NIC8    NIC9    NIC10   CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV18    NV18    NV18    NV18    NV18    NV18    NV18    SYS     SYS     PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU1    NV18     X      NV18    NV18    NV18    NV18    NV18    NV18    SYS     SYS     NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU2    NV18    NV18     X      NV18    NV18    NV18    NV18    NV18    SYS     SYS     NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU3    NV18    NV18    NV18     X      NV18    NV18    NV18    NV18    SYS     SYS     NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     NODE    0-63,128-191    0               N/A
GPU4    NV18    NV18    NV18    NV18     X      NV18    NV18    NV18    NODE    NODE    SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    SYS     64-127,192-255  1               N/A
GPU5    NV18    NV18    NV18    NV18    NV18     X      NV18    NV18    NODE    NODE    SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    SYS     64-127,192-255  1               N/A
GPU6    NV18    NV18    NV18    NV18    NV18    NV18     X      NV18    NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    SYS     64-127,192-255  1               N/A
GPU7    NV18    NV18    NV18    NV18    NV18    NV18    NV18     X      NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     SYS     64-127,192-255  1               N/A
NIC0    SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE     X      PIX     SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS
NIC1    SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    PIX      X      SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS
NIC2    PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS      X      NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE
NIC3    NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE     X      NODE    NODE    SYS     SYS     SYS     SYS     NODE
NIC4    NODE    NODE    PIX     NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE     X      NODE    SYS     SYS     SYS     SYS     NODE
NIC5    NODE    NODE    NODE    PIX     SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE    NODE     X      SYS     SYS     SYS     SYS     NODE
NIC6    SYS     SYS     SYS     SYS     PIX     NODE    NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS      X      NODE    NODE    NODE    SYS
NIC7    SYS     SYS     SYS     SYS     NODE    PIX     NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE     X      NODE    NODE    SYS
NIC8    SYS     SYS     SYS     SYS     NODE    NODE    PIX     NODE    NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE     X      NODE    SYS
NIC9    SYS     SYS     SYS     SYS     NODE    NODE    NODE    PIX     NODE    NODE    SYS     SYS     SYS     SYS     NODE    NODE    NODE     X      SYS
NIC10   NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS     SYS     SYS     NODE    NODE    NODE    NODE    SYS     SYS     SYS     SYS      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_12
  NIC1: mlx5_13
  NIC2: mlx5_gdr_0
  NIC3: mlx5_gdr_1
  NIC4: mlx5_gdr_2
  NIC5: mlx5_gdr_3
  NIC6: mlx5_gdr_4
  NIC7: mlx5_gdr_5
  NIC8: mlx5_gdr_6
  NIC9: mlx5_gdr_7
  NIC10: mlx5_bond_0

==============================
     Environment Variables
==============================
NVIDIA_VISIBLE_DEVICES=all
NVIDIA_REQUIRE_CUDA=cuda>=13.0 brand=unknown,driver>=535,driver<536 brand=grid,driver>=535,driver<536 brand=tesla,driver>=535,driver<536 brand=nvidia,driver>=535,driver<536 brand=quadro,driver>=535,driver<536 brand=quadrortx,driver>=535,driver<536 brand=nvidiartx,driver>=535,driver<536 brand=vapps,driver>=535,driver<536 brand=vpc,driver>=535,driver<536 brand=vcs,driver>=535,driver<536 brand=vws,driver>=535,driver<536 brand=cloudgaming,driver>=535,driver<536 brand=unknown,driver>=550,driver<551 brand=grid,driver>=550,driver<551 brand=tesla,driver>=550,driver<551 brand=nvidia,driver>=550,driver<551 brand=quadro,driver>=550,driver<551 brand=quadrortx,driver>=550,driver<551 brand=nvidiartx,driver>=550,driver<551 brand=vapps,driver>=550,driver<551 brand=vpc,driver>=550,driver<551 brand=vcs,driver>=550,driver<551 brand=vws,driver>=550,driver<551 brand=cloudgaming,driver>=550,driver<551 brand=unknown,driver>=565,driver<566 brand=grid,driver>=565,driver<566 brand=tesla,driver>=565,driver<566 brand=nvidia,driver>=565,driver<566 brand=quadro,driver>=565,driver<566 brand=quadrortx,driver>=565,driver<566 brand=nvidiartx,driver>=565,driver<566 brand=vapps,driver>=565,driver<566 brand=vpc,driver>=565,driver<566 brand=vcs,driver>=565,driver<566 brand=vws,driver>=565,driver<566 brand=cloudgaming,driver>=565,driver<566 brand=unknown,driver>=570,driver<571 brand=grid,driver>=570,driver<571 brand=tesla,driver>=570,driver<571 brand=nvidia,driver>=570,driver<571 brand=quadro,driver>=570,driver<571 brand=quadrortx,driver>=570,driver<571 brand=nvidiartx,driver>=570,driver<571 brand=vapps,driver>=570,driver<571 brand=vpc,driver>=570,driver<571 brand=vcs,driver>=570,driver<571 brand=vws,driver>=570,driver<571 brand=cloudgaming,driver>=570,driver<571 brand=unknown,driver>=575,driver<576 brand=grid,driver>=575,driver<576 brand=tesla,driver>=575,driver<576 brand=nvidia,driver>=575,driver<576 brand=quadro,driver>=575,driver<576 brand=quadrortx,driver>=575,driver<576 brand=nvidiartx,driver>=575,driver<576 brand=vapps,driver>=575,driver<576 brand=vpc,driver>=575,driver<576 brand=vcs,driver>=575,driver<576 brand=vws,driver>=575,driver<576 brand=cloudgaming,driver>=575,driver<576
TORCH_CUDA_ARCH_LIST=7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX
NVIDIA_DRIVER_CAPABILITIES=compute,utility
VLLM_USAGE_SOURCE=production-docker-image
CUDA_VERSION=13.0.2
VLLM_ENABLE_CUDA_COMPATIBILITY=0
VLLM_ENGINE_READY_TIMEOUT_S=3600
LD_LIBRARY_PATH=/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_root
</details>

🐛 Describe the bug

We deploy the model using the following script and send concurrent requests with identical inputs via claude code -p. When cudagraph_mode is set to FULL_DECODE_ONLY, some requests produce garbled output, while single-request (non-concurrent) inference works fine. When cudagraph_mode is set to None, the garbled output under concurrency disappears.

IMAGE=vllm/vllm-openai:nightly

docker run -d \
  --gpus all \
  --name vllm-deepseek_v4 \
  -p 8000:8000 \
  --restart unless-stopped \
  -e VLLM_ENGINE_READY_TIMEOUT_S=3600 \
  -e VLLM_API_KEY=xxxx \
  -v $PROJ/models/deepseek-ai/DeepSeek-V4-Pro:/model \
  $IMAGE \
  --enable-prefix-caching \
  --enable-chunked-prefill \
  --model /model \
  --served-model-name inner-deepseek_v4 \
  --enable-expert-parallel \
  --tensor-parallel-size 8 \
  --host 0.0.0.0 \
  --port 8000 \
  --trust-remote-code \
  --gpu-memory-utilization 0.95 \
  --max-num-seqs 128 \
  --kv-cache-dtype fp8 \
  --block-size 256 \
  --compilation-config '{"mode":0,"cudagraph_mode":"FULL_DECODE_ONLY"}' \
  --attention_config.use_fp4_indexer_cache=True \
  --tokenizer-mode deepseek_v4 \
  --tool-call-parser deepseek_v4 \
  --enable-auto-tool-choice \
  --reasoning-parser deepseek_v4

This issue can be reproduced using the following setup/steps. The test input is in prompt.txt, with the following content:

Please give me the proof of Fermat's Little Theorem
for i in 1 2 3 4; do;  claude -p --output-format stream-json --verbose < prompt.txt > out-short-${i}.jsonl &; done; wait

Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

extent analysis

TL;DR

The issue of garbled output under concurrent requests with cudagraph_mode set to FULL_DECODE_ONLY may be related to the CUDA graph configuration and can potentially be resolved by adjusting the compilation config or the environment variables related to CUDA and GPU utilization.

Guidance

  • Verify that the CUDA version and driver are compatible with the PyTorch version being used.
  • Check the GPU memory utilization and adjust the --gpu-memory-utilization parameter to ensure sufficient memory is allocated for concurrent requests.
  • Experiment with different cudagraph_mode settings or disable it to see if the issue persists.
  • Review the environment variables, such as TORCH_CUDA_ARCH_LIST and NVIDIA_VISIBLE_DEVICES, to ensure they are correctly configured for the GPU setup.

Example

No specific code example is provided, but the user can try modifying the compilation-config parameter in the Docker run command to adjust the cudagraph_mode or add other configuration options.

Notes

The issue may be specific to the FULL_DECODE_ONLY mode and the concurrent request setup. Further investigation is needed to determine the root cause and the most effective solution.

Recommendation

Apply workaround by adjusting the cudagraph_mode setting or disabling it to resolve the garbled output issue under concurrent requests.

Vote matrix · Quick signals

Works
Did the solution work? Tap to confirm.
Easy Fix
Was it a quick fix?
Time Saver
Did it save you time?
Blocking
Was it severely blocking?
Common Issue
Are others likely hitting this too?
Flaky / Intermittent
Is it intermittent?
Verified / Reproducible
Can you reproduce it reliably?
Loading…

Still need to ship something?

×6

Another batch ranked right after the header list — different links, same matching logic.

Back to top recommendations

TRENDING

vllm - 💡(How to fix) Fix [Bug]: Garbled Output in DeepSeek-V4 with CUDA Graph Enabled Under Concurrent Identical Input Requests [1 participants]