vllm - 💡(How to fix) Fix [Bug]: `renderer_num_workers` ignored by offline `LLM` (only affects async serving)

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Fix Action

Fix / Workaround

============================== 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): 256 On-line CPU(s) list: 0-255 Vendor ID: AuthenticAMD Model name: AMD EPYC 7763 64-Core Processor CPU family: 25 Model: 1 Thread(s) per core: 2 Core(s) per socket: 64 Socket(s): 2 Stepping: 1 Frequency boost: enabled CPU max MHz: 3530.4929 CPU min MHz: 1500.0000 BogoMIPS: 4899.82 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 nopl 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 cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm ibpb_exit_to_user Virtualization: AMD-V L1d cache: 4 MiB (128 instances) L1i cache: 4 MiB (128 instances) L2 cache: 64 MiB (128 instances) L3 cache: 512 MiB (16 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 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 and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsa: Vulnerable: Clear CPU buffers attempted, no microcode Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

Code Example

collect_env.py      100%[=================>]  34.27K  --.-KB/s    in 0.002s  

2026-05-17 19:03:25 (16.8 MB/s) - ‘collect_env.py’ saved [35090/35090]

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                : version 3.22.1
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu128
Is debug build               : False
CUDA used to build PyTorch   : 12.8
ROCM used to build PyTorch   : N/A
XPU used to build PyTorch    : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.10 (main, Apr  9 2025, 04:03:51) [Clang 20.1.0 ] (64-bit runtime)
Python platform              : Linux-5.15.0-170-generic-x86_64-with-glibc2.35
    
==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 12.2.140
CUDA_MODULE_LOADING set to   : 
GPU models and configuration : 
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB

Nvidia driver version        : 550.54.15
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):                                  256
On-line CPU(s) list:                     0-255
Vendor ID:                               AuthenticAMD
Model name:                              AMD EPYC 7763 64-Core Processor
CPU family:                              25
Model:                                   1
Thread(s) per core:                      2
Core(s) per socket:                      64
Socket(s):                               2
Stepping:                                1
Frequency boost:                         enabled
CPU max MHz:                             3530.4929
CPU min MHz:                             1500.0000
BogoMIPS:                                4899.82
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 nopl 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 cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm ibpb_exit_to_user
Virtualization:                          AMD-V
L1d cache:                               4 MiB (128 instances)
L1i cache:                               4 MiB (128 instances)
L2 cache:                                64 MiB (128 instances)
L3 cache:                                512 MiB (16 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 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 and seccomp
Vulnerability Spectre v1:                Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:                Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                     Not affected
Vulnerability Tsa:                       Vulnerable: Clear CPU buffers attempted, no microcode
Vulnerability Tsx async abort:           Not affected
Vulnerability Vmscape:                   Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-cufile-cu12==1.13.1.3
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.0
[pip3] nvidia-cutlass-dsl-libs-base==4.4.0
[pip3] nvidia-ml-py==13.590.48
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0
[pip3] torchaudio==2.10.0
[pip3] torchvision==0.25.0
[pip3] transformers==5.7.0
[pip3] triton==3.6.0
[conda] cuda-cccl_linux-64             12.9.27                      0                   nvidia
[conda] cuda-command-line-tools        12.6.2                       0                   nvidia
[conda] cuda-compiler                  12.6.2                       0                   nvidia
[conda] cuda-crt-dev_linux-64          12.9.86                      0                   nvidia
[conda] cuda-cudart                    12.9.79                      0                   nvidia
[conda] cuda-cudart-dev                12.9.79                      0                   nvidia
[conda] cuda-cudart-dev_linux-64       12.9.79                      0                   nvidia
[conda] cuda-cudart-static             12.9.79                      0                   nvidia
[conda] cuda-cudart-static_linux-64    12.9.79                      0                   nvidia
[conda] cuda-cudart_linux-64           12.9.79                      0                   nvidia
[conda] cuda-cuobjdump                 12.9.82                      1                   nvidia
[conda] cuda-cupti                     12.9.79                      0                   nvidia
[conda] cuda-cupti-dev                 12.9.79                      0                   nvidia
[conda] cuda-cuxxfilt                  12.9.82                      1                   nvidia
[conda] cuda-driver-dev                12.9.79                      0                   nvidia
[conda] cuda-driver-dev_linux-64       12.9.79                      0                   nvidia
[conda] cuda-gdb                       12.9.79                      1                   nvidia
[conda] cuda-libraries                 12.6.2                       0                   nvidia
[conda] cuda-libraries-dev             12.6.2                       0                   nvidia
[conda] cuda-nsight                    12.9.79                      0                   nvidia
[conda] cuda-nvcc                      12.2.140                     0                   nvidia
[conda] cuda-nvdisasm                  12.9.88                      1                   nvidia
[conda] cuda-nvml-dev                  12.9.79                      1                   nvidia
[conda] cuda-nvprof                    12.9.79                      0                   nvidia
[conda] cuda-nvprune                   12.9.82                      1                   nvidia
[conda] cuda-nvrtc                     12.9.86                      0                   nvidia
[conda] cuda-nvrtc-dev                 12.9.86                      0                   nvidia
[conda] cuda-nvtx                      12.9.79                      0                   nvidia
[conda] cuda-nvvp                      12.9.79                      1                   nvidia
[conda] cuda-opencl                    12.9.19                      0                   nvidia
[conda] cuda-opencl-dev                12.9.19                      0                   nvidia
[conda] cuda-profiler-api              12.9.79                      0                   nvidia
[conda] cuda-sanitizer-api             12.9.79                      1                   nvidia
[conda] cuda-toolkit                   12.6.2                       0                   nvidia
[conda] cuda-tools                     12.6.2                       0                   nvidia
[conda] cuda-version                   12.9                         3                   nvidia
[conda] cuda-visual-tools              12.6.2                       0                   nvidia
[conda] gds-tools                      1.14.1.1                     4                   nvidia
[conda] libcublas                      12.9.1.4                     0                   nvidia
[conda] libcublas-dev                  12.9.1.4                     0                   nvidia
[conda] libcufft                       11.4.1.4                     0                   nvidia
[conda] libcufft-dev                   11.4.1.4                     0                   nvidia
[conda] libcufile                      1.14.1.1                     4                   nvidia
[conda] libcufile-dev                  1.14.1.1                     4                   nvidia
[conda] libcurand                      10.3.10.19                   0                   nvidia
[conda] libcurand-dev                  10.3.10.19                   0                   nvidia
[conda] libcusolver                    11.7.5.82                    0                   nvidia
[conda] libcusolver-dev                11.7.5.82                    0                   nvidia
[conda] libcusparse                    12.5.10.65                   0                   nvidia
[conda] libcusparse-dev                12.5.10.65                   0                   nvidia
[conda] libnpp                         12.4.1.87                    0                   nvidia
[conda] libnpp-dev                     12.4.1.87                    0                   nvidia
[conda] libnvfatbin                    12.9.82                      0                   nvidia
[conda] libnvfatbin-dev                12.9.82                      0                   nvidia
[conda] libnvjitlink                   12.9.86                      0                   nvidia
[conda] libnvjitlink-dev               12.9.86                      0                   nvidia
[conda] libnvjpeg                      12.4.0.76                    0                   nvidia
[conda] libnvjpeg-dev                  12.4.0.76                    0                   nvidia
[conda] nsight-compute                 2025.2.1.3                   0                   nvidia
[conda] numpy                          2.3.3                        pypi_0              pypi
[conda] nvidia-cublas-cu12             12.8.4.1                     pypi_0              pypi
[conda] nvidia-cuda-cupti-cu12         12.8.90                      pypi_0              pypi
[conda] nvidia-cuda-nvrtc-cu12         12.8.93                      pypi_0              pypi
[conda] nvidia-cuda-runtime-cu12       12.8.90                      pypi_0              pypi
[conda] nvidia-cudnn-cu12              9.10.2.21                    pypi_0              pypi
[conda] nvidia-cufft-cu12              11.3.3.83                    pypi_0              pypi
[conda] nvidia-cufile-cu12             1.13.1.3                     pypi_0              pypi
[conda] nvidia-curand-cu12             10.3.9.90                    pypi_0              pypi
[conda] nvidia-cusolver-cu12           11.7.3.90                    pypi_0              pypi
[conda] nvidia-cusparse-cu12           12.5.8.93                    pypi_0              pypi
[conda] nvidia-cusparselt-cu12         0.7.1                        pypi_0              pypi
[conda] nvidia-ml-py                   13.580.65                    pypi_0              pypi
[conda] nvidia-nccl-cu12               2.27.3                       pypi_0              pypi
[conda] nvidia-nvjitlink-cu12          12.8.93                      pypi_0              pypi
[conda] nvidia-nvtx-cu12               12.8.90                      pypi_0              pypi
[conda] torch                          2.8.0                        pypi_0              pypi
[conda] transformers                   4.57.0                       pypi_0              pypi
[conda] triton                         3.4.0                        pypi_0              pypi

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.16.0rc2.dev345+g0e22cd618.d20260221 (git sha: 0e22cd618, date: 20260221)
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    CPU Affinity  NUMA Affinity   GPU NUMA ID
GPU0     X      NV12    NV12    NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU1    NV12     X      NV12    NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU2    NV12    NV12     X      NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU3    NV12    NV12    NV12     X      NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU4    NV12    NV12    NV12    NV12     X      NV12    NV12    NV12    64-127,192-255        1               N/A
GPU5    NV12    NV12    NV12    NV12    NV12     X      NV12    NV12    64-127,192-255        1               N/A
GPU6    NV12    NV12    NV12    NV12    NV12    NV12     X      NV12    64-127,192-255        1               N/A
GPU7    NV12    NV12    NV12    NV12    NV12    NV12    NV12     X      64-127,192-255        1               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
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_hzz5361
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
collect_env.py      100%[=================>]  34.27K  --.-KB/s    in 0.002s  

2026-05-17 19:03:25 (16.8 MB/s) - ‘collect_env.py’ saved [35090/35090]

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                : version 3.22.1
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu128
Is debug build               : False
CUDA used to build PyTorch   : 12.8
ROCM used to build PyTorch   : N/A
XPU used to build PyTorch    : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.10 (main, Apr  9 2025, 04:03:51) [Clang 20.1.0 ] (64-bit runtime)
Python platform              : Linux-5.15.0-170-generic-x86_64-with-glibc2.35
    
==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : 12.2.140
CUDA_MODULE_LOADING set to   : 
GPU models and configuration : 
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB

Nvidia driver version        : 550.54.15
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):                                  256
On-line CPU(s) list:                     0-255
Vendor ID:                               AuthenticAMD
Model name:                              AMD EPYC 7763 64-Core Processor
CPU family:                              25
Model:                                   1
Thread(s) per core:                      2
Core(s) per socket:                      64
Socket(s):                               2
Stepping:                                1
Frequency boost:                         enabled
CPU max MHz:                             3530.4929
CPU min MHz:                             1500.0000
BogoMIPS:                                4899.82
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 nopl 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 cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold v_vmsave_vmload vgif v_spec_ctrl umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor smca fsrm ibpb_exit_to_user
Virtualization:                          AMD-V
L1d cache:                               4 MiB (128 instances)
L1i cache:                               4 MiB (128 instances)
L2 cache:                                64 MiB (128 instances)
L3 cache:                                512 MiB (16 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 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 and seccomp
Vulnerability Spectre v1:                Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:                Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                     Not affected
Vulnerability Tsa:                       Vulnerable: Clear CPU buffers attempted, no microcode
Vulnerability Tsx async abort:           Not affected
Vulnerability Vmscape:                   Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-cufile-cu12==1.13.1.3
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.0
[pip3] nvidia-cutlass-dsl-libs-base==4.4.0
[pip3] nvidia-ml-py==13.590.48
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0
[pip3] torchaudio==2.10.0
[pip3] torchvision==0.25.0
[pip3] transformers==5.7.0
[pip3] triton==3.6.0
[conda] cuda-cccl_linux-64             12.9.27                      0                   nvidia
[conda] cuda-command-line-tools        12.6.2                       0                   nvidia
[conda] cuda-compiler                  12.6.2                       0                   nvidia
[conda] cuda-crt-dev_linux-64          12.9.86                      0                   nvidia
[conda] cuda-cudart                    12.9.79                      0                   nvidia
[conda] cuda-cudart-dev                12.9.79                      0                   nvidia
[conda] cuda-cudart-dev_linux-64       12.9.79                      0                   nvidia
[conda] cuda-cudart-static             12.9.79                      0                   nvidia
[conda] cuda-cudart-static_linux-64    12.9.79                      0                   nvidia
[conda] cuda-cudart_linux-64           12.9.79                      0                   nvidia
[conda] cuda-cuobjdump                 12.9.82                      1                   nvidia
[conda] cuda-cupti                     12.9.79                      0                   nvidia
[conda] cuda-cupti-dev                 12.9.79                      0                   nvidia
[conda] cuda-cuxxfilt                  12.9.82                      1                   nvidia
[conda] cuda-driver-dev                12.9.79                      0                   nvidia
[conda] cuda-driver-dev_linux-64       12.9.79                      0                   nvidia
[conda] cuda-gdb                       12.9.79                      1                   nvidia
[conda] cuda-libraries                 12.6.2                       0                   nvidia
[conda] cuda-libraries-dev             12.6.2                       0                   nvidia
[conda] cuda-nsight                    12.9.79                      0                   nvidia
[conda] cuda-nvcc                      12.2.140                     0                   nvidia
[conda] cuda-nvdisasm                  12.9.88                      1                   nvidia
[conda] cuda-nvml-dev                  12.9.79                      1                   nvidia
[conda] cuda-nvprof                    12.9.79                      0                   nvidia
[conda] cuda-nvprune                   12.9.82                      1                   nvidia
[conda] cuda-nvrtc                     12.9.86                      0                   nvidia
[conda] cuda-nvrtc-dev                 12.9.86                      0                   nvidia
[conda] cuda-nvtx                      12.9.79                      0                   nvidia
[conda] cuda-nvvp                      12.9.79                      1                   nvidia
[conda] cuda-opencl                    12.9.19                      0                   nvidia
[conda] cuda-opencl-dev                12.9.19                      0                   nvidia
[conda] cuda-profiler-api              12.9.79                      0                   nvidia
[conda] cuda-sanitizer-api             12.9.79                      1                   nvidia
[conda] cuda-toolkit                   12.6.2                       0                   nvidia
[conda] cuda-tools                     12.6.2                       0                   nvidia
[conda] cuda-version                   12.9                         3                   nvidia
[conda] cuda-visual-tools              12.6.2                       0                   nvidia
[conda] gds-tools                      1.14.1.1                     4                   nvidia
[conda] libcublas                      12.9.1.4                     0                   nvidia
[conda] libcublas-dev                  12.9.1.4                     0                   nvidia
[conda] libcufft                       11.4.1.4                     0                   nvidia
[conda] libcufft-dev                   11.4.1.4                     0                   nvidia
[conda] libcufile                      1.14.1.1                     4                   nvidia
[conda] libcufile-dev                  1.14.1.1                     4                   nvidia
[conda] libcurand                      10.3.10.19                   0                   nvidia
[conda] libcurand-dev                  10.3.10.19                   0                   nvidia
[conda] libcusolver                    11.7.5.82                    0                   nvidia
[conda] libcusolver-dev                11.7.5.82                    0                   nvidia
[conda] libcusparse                    12.5.10.65                   0                   nvidia
[conda] libcusparse-dev                12.5.10.65                   0                   nvidia
[conda] libnpp                         12.4.1.87                    0                   nvidia
[conda] libnpp-dev                     12.4.1.87                    0                   nvidia
[conda] libnvfatbin                    12.9.82                      0                   nvidia
[conda] libnvfatbin-dev                12.9.82                      0                   nvidia
[conda] libnvjitlink                   12.9.86                      0                   nvidia
[conda] libnvjitlink-dev               12.9.86                      0                   nvidia
[conda] libnvjpeg                      12.4.0.76                    0                   nvidia
[conda] libnvjpeg-dev                  12.4.0.76                    0                   nvidia
[conda] nsight-compute                 2025.2.1.3                   0                   nvidia
[conda] numpy                          2.3.3                        pypi_0              pypi
[conda] nvidia-cublas-cu12             12.8.4.1                     pypi_0              pypi
[conda] nvidia-cuda-cupti-cu12         12.8.90                      pypi_0              pypi
[conda] nvidia-cuda-nvrtc-cu12         12.8.93                      pypi_0              pypi
[conda] nvidia-cuda-runtime-cu12       12.8.90                      pypi_0              pypi
[conda] nvidia-cudnn-cu12              9.10.2.21                    pypi_0              pypi
[conda] nvidia-cufft-cu12              11.3.3.83                    pypi_0              pypi
[conda] nvidia-cufile-cu12             1.13.1.3                     pypi_0              pypi
[conda] nvidia-curand-cu12             10.3.9.90                    pypi_0              pypi
[conda] nvidia-cusolver-cu12           11.7.3.90                    pypi_0              pypi
[conda] nvidia-cusparse-cu12           12.5.8.93                    pypi_0              pypi
[conda] nvidia-cusparselt-cu12         0.7.1                        pypi_0              pypi
[conda] nvidia-ml-py                   13.580.65                    pypi_0              pypi
[conda] nvidia-nccl-cu12               2.27.3                       pypi_0              pypi
[conda] nvidia-nvjitlink-cu12          12.8.93                      pypi_0              pypi
[conda] nvidia-nvtx-cu12               12.8.90                      pypi_0              pypi
[conda] torch                          2.8.0                        pypi_0              pypi
[conda] transformers                   4.57.0                       pypi_0              pypi
[conda] triton                         3.4.0                        pypi_0              pypi

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.16.0rc2.dev345+g0e22cd618.d20260221 (git sha: 0e22cd618, date: 20260221)
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
        GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    CPU Affinity  NUMA Affinity   GPU NUMA ID
GPU0     X      NV12    NV12    NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU1    NV12     X      NV12    NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU2    NV12    NV12     X      NV12    NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU3    NV12    NV12    NV12     X      NV12    NV12    NV12    NV12    0-63,128-191  0               N/A
GPU4    NV12    NV12    NV12    NV12     X      NV12    NV12    NV12    64-127,192-255        1               N/A
GPU5    NV12    NV12    NV12    NV12    NV12     X      NV12    NV12    64-127,192-255        1               N/A
GPU6    NV12    NV12    NV12    NV12    NV12    NV12     X      NV12    64-127,192-255        1               N/A
GPU7    NV12    NV12    NV12    NV12    NV12    NV12    NV12     X      64-127,192-255        1               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
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_hzz5361
</details>

🐛 Describe the bug

Version: vllm main @ 966903eb9 (2026-05-17), verified against source.

Summary: For offline LLM.generate/.chat, renderer_num_workers > 1 does not parallelize multimodal preprocessing — it has no effect.

Why: The thread pool sized by renderer_num_workers (BaseRenderer._executor) is only ever consumed by _process_multimodal_async, which is reached exclusively through the async path (render_chat_async). Offline LLM calls the sync render_chat, which calls _process_multimodal directly, so mm_processor.apply runs serially on the calling thread, one prompt at a time. The pool is constructed and never submitted to. (Default is 1; with the mm processor cache enabled, >1 is rejected at config time instead.)

Docs: The renderer_num_workers docstring says it "handles ... multimodal preprocessing" with no note that this applies to async serving only — so on a preprocessing-bound offline batch it's a silent no-op.

Question: Is the serial offline path intended? If so, the docstring should state that renderer_num_workers only affects async serving. If not, would a one-time warning when it's set >1 under offline LLM be welcome?

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