[Usage]: Unable to load Mistral-Small-3.2-24B-Instruct-2506-FP8 due to "Value error, Found unknown quantization", but the same configs worked for vllm v0.11.0 #34028
Description
Your current environment
python collect_env.py
--2026-02-06 23:27:52-- https://raw.githubusercontent.com/vllm-project/vllm/main/vllm/collect_env.py
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 27835 (27K) [text/plain]
Saving to: ‘collect_env.py’
collect_env.py 100%[=====================================================================================================================================================>] 27.18K --.-KB/s in 0.001s
2026-02-06 23:27:52 (37.3 MB/s) - ‘collect_env.py’ saved [27835/27835]
Collecting environment information...
uv is set
==============================
System Info
==============================
OS : Rocky Linux 9.7 (Blue Onyx) (x86_64)
GCC version : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-11)
Clang version : Could not collect
CMake version : Could not collect
Libc version : glibc-2.34
==============================
PyTorch Info
==============================
PyTorch version : 2.9.1+cu128
Is debug build : False
CUDA used to build PyTorch : 12.8
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.5 (main, Aug 14 2024, 05:08:31) [Clang 18.1.8 ] (64-bit runtime)
Python platform : Linux-6.8.0-90-generic-x86_64-with-glibc2.34
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : 12.8.93
CUDA_MODULE_LOADING set to :
GPU models and configuration : GPU 0: NVIDIA L40S
Nvidia driver version : 550.127.08
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: 48 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 8
On-line CPU(s) list: 0-7
Vendor ID: AuthenticAMD
Model name: AMD EPYC 7413 24-Core Processor
CPU family: 25
Model: 1
Thread(s) per core: 1
Core(s) per socket: 8
Socket(s): 1
Stepping: 1
BogoMIPS: 5300.00
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 rep_good nopl cpuid extd_apicid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy svm cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw perfctr_core ssbd ibrs ibpb stibp vmmcall fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves clzero xsaveerptr wbnoinvd arat npt lbrv nrip_save tsc_scale vmcb_clean pausefilter pfthreshold v_vmsave_vmload vgif umip pku ospke vaes vpclmulqdq rdpid overflow_recov succor fsrm arch_capabilities
Virtualization: AMD-V
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 512 KiB (8 instances)
L1i cache: 512 KiB (8 instances)
L2 cache: 4 MiB (8 instances)
L3 cache: 128 MiB (8 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-7
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: Vulnerable: Safe RET, no microcode
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; Retpolines; IBPB conditional; IBRS_FW; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Not affected
==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.1
[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==4.3.5
[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==3.3.20
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.9.1
[pip3] torchaudio==2.9.1
[pip3] torchvision==0.24.1
[pip3] transformers==4.57.6
[pip3] triton==3.5.1
[conda] Could not collect
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.15.1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
GPU0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X 0-7 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
==============================
NVIDIA_VISIBLE_DEVICES=all
NVIDIA_REQUIRE_CUDA=cuda>=12.8 brand=unknown,driver>=470,driver<471 brand=grid,driver>=470,driver<471 brand=tesla,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=vapps,driver>=470,driver<471 brand=vpc,driver>=470,driver<471 brand=vcs,driver>=470,driver<471 brand=vws,driver>=470,driver<471 brand=cloudgaming,driver>=470,driver<471 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>=560,driver<561 brand=grid,driver>=560,driver<561 brand=tesla,driver>=560,driver<561 brand=nvidia,driver>=560,driver<561 brand=quadro,driver>=560,driver<561 brand=quadrortx,driver>=560,driver<561 brand=nvidiartx,driver>=560,driver<561 brand=vapps,driver>=560,driver<561 brand=vpc,driver>=560,driver<561 brand=vcs,driver>=560,driver<561 brand=vws,driver>=560,driver<561 brand=cloudgaming,driver>=560,driver<561 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
NCCL_VERSION=2.25.1
NVIDIA_DRIVER_CAPABILITIES=compute,utility
NVIDIA_PRODUCT_NAME=CUDA
CUDA_VERSION=12.8.1
VLLM_CONFIGURE_LOGGING=1
LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/cuda/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
How would you like to use vllm
Hey !
I am encountering this issue using v0.15.1, have we changed the way we load models in v0.15.1?
Thanks in advance for your help!
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325]
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325] █ █ █▄ ▄█
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.15.1
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325] █▄█▀ █ █ █ █ model stelterlab/Mistral-Small-3.2-24B-Instruct-2506-FP8
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:325]
(APIServer pid=44) INFO 02-06 23:24:30 [utils.py:261] non-default args: {'model_tag': 'stelterlab/Mistral-Small-3.2-24B-Instruct-2506-FP8', 'api_server_count': 1, 'host': '0.0.0.0', 'port': 30000, 'enable_auto_tool_choice': True, 'tool_call_parser': 'mistral', 'model': 'stelterlab/Mistral-Small-3.2-24B-Instruct-2506-FP8', 'tokenizer_mode': 'mistral', 'dtype': 'bfloat16', 'max_model_len': 32768, 'served_model_name': ['mistral-llm'], 'config_format': 'mistral', 'hf_token': 'XXXXX', 'load_format': 'mistral', 'gpu_memory_utilization': 0.7, 'limit_mm_per_prompt': {'image': 4}, 'max_num_seqs': 10}
(APIServer pid=44) WARNING 02-06 23:24:30 [system_utils.py:266] Found ulimit of 32768 and failed to automatically increase with error current limit exceeds maximum limit. This can cause fd limit errors like `OSError: [Errno 24] Too many open files`. Consider increasing with ulimit -n
(APIServer pid=44) Traceback (most recent call last):
(APIServer pid=44) File "/app/.venv/bin/vllm", line 10, in <module>
(APIServer pid=44) sys.exit(main())
(APIServer pid=44) ^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/cli/main.py", line 73, in main
(APIServer pid=44) args.dispatch_function(args)
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/cli/serve.py", line 111, in cmd
(APIServer pid=44) uvloop.run(run_server(args))
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/uvloop/__init__.py", line 96, in run
(APIServer pid=44) return __asyncio.run(
(APIServer pid=44) ^^^^^^^^^^^^^^
(APIServer pid=44) File "/root/.local/share/uv/python/cpython-3.12.5-linux-x86_64-gnu/lib/python3.12/asyncio/runners.py", line 194, in run
(APIServer pid=44) return runner.run(main)
(APIServer pid=44) ^^^^^^^^^^^^^^^^
(APIServer pid=44) File "/root/.local/share/uv/python/cpython-3.12.5-linux-x86_64-gnu/lib/python3.12/asyncio/runners.py", line 118, in run
(APIServer pid=44) return self._loop.run_until_complete(task)
(APIServer pid=44) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=44) File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/uvloop/__init__.py", line 48, in wrapper
(APIServer pid=44) return await main
(APIServer pid=44) ^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 919, in run_server
(APIServer pid=44) await run_server_worker(listen_address, sock, args, **uvicorn_kwargs)
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 938, in run_server_worker
(APIServer pid=44) async with build_async_engine_client(
(APIServer pid=44) File "/root/.local/share/uv/python/cpython-3.12.5-linux-x86_64-gnu/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=44) return await anext(self.gen)
(APIServer pid=44) ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 147, in build_async_engine_client
(APIServer pid=44) async with build_async_engine_client_from_engine_args(
(APIServer pid=44) File "/root/.local/share/uv/python/cpython-3.12.5-linux-x86_64-gnu/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=44) return await anext(self.gen)
(APIServer pid=44) ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 173, in build_async_engine_client_from_engine_args
(APIServer pid=44) vllm_config = engine_args.create_engine_config(usage_context=usage_context)
(APIServer pid=44) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/engine/arg_utils.py", line 1374, in create_engine_config
(APIServer pid=44) model_config = self.create_model_config()
(APIServer pid=44) ^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/vllm/engine/arg_utils.py", line 1228, in create_model_config
(APIServer pid=44) return ModelConfig(
(APIServer pid=44) ^^^^^^^^^^^^
(APIServer pid=44) File "/app/.venv/lib/python3.12/site-packages/pydantic/_internal/_dataclasses.py", line 121, in __init__
(APIServer pid=44) s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s)
(APIServer pid=44) pydantic_core._pydantic_core.ValidationError: 1 validation error for ModelConfig
(APIServer pid=44) Value error, Found unknown quantization='{'config_groups': {'group_0': {'input_activations': {'dynamic': True, 'num_bits': 8, 'observer': None, 'strategy': 'token', 'symmetric': True, 'type': 'float'}, 'targets': ['Linear'], 'weights': {'dynamic': False, 'num_bits': 8, 'observer': 'minmax', 'strategy': 'tensor', 'symmetric': True, 'type': 'float'}}}, 'format': 'float-quantized', 'ignore': ['lm_head', 'output'], 'quant_method': 'compressed-tensors', 'quantization_status': 'compressed'}' in config [type=value_error, input_value=ArgsKwargs((), {'model': ...rocessor_plugin': None}), input_type=ArgsKwargs]
(APIServer pid=44) For further information visit https://errors.pydantic.dev/2.12/v/value_error
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