[Bug]: GGUF model with architecture olmo2 is not supported yet #30691
Description
Your current environment
The output of vllm serve Olmo-3-32B-Think-Q8_0.gguf
Collecting environment information...
==============================
System Info
==============================
OS : Ubuntu 22.04.5 LTS (x86_64)
GCC version : (Ubuntu 11.4.0-1ubuntu1~22.04.2) 11.4.0
Clang version : Could not collect
CMake version : Could not collect
Libc version : glibc-2.35
==============================
PyTorch Info
==============================
PyTorch version : 2.9.0+cu129
Is debug build : False
CUDA used to build PyTorch : 12.9
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.12 (main, Oct 10 2025, 08:52:57) [GCC 11.4.0] (64-bit runtime)
Python platform : Linux-4.18.0-553.83.1.el8_10.x86_64-x86_64-with-glibc2.35
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : 12.9.86
CUDA_MODULE_LOADING set to :
GPU models and configuration :
GPU 0: NVIDIA L40S-48C
GPU 1: NVIDIA L40S-48C
Nvidia driver version : 535.129.03
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: 43 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 16
On-line CPU(s) list: 0-15
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Platinum 8462Y+
CPU family: 6
Model: 143
Thread(s) per core: 1
Core(s) per socket: 2
Socket(s): 8
Stepping: 8
BogoMIPS: 5599.99
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xsaves arat pku ospke md_clear flush_l1d arch_capabilities
Hypervisor vendor: VMware
Virtualization type: full
L1d cache: 768 KiB (16 instances)
L1i cache: 512 KiB (16 instances)
L2 cache: 32 MiB (16 instances)
L3 cache: 480 MiB (8 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-15
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Unknown: No mitigations
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
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Not affected
==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.5.3
[pip3] numpy==2.2.0
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.16.0
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.3.1
[pip3] nvidia-ml-py==13.580.82
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvshmem-cu12==3.3.20
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] pyzmq==27.1.0
[pip3] torch==2.9.0+cu129
[pip3] torchaudio==2.9.0+cu129
[pip3] torchvision==0.24.0+cu129
[pip3] transformers==4.57.3
[pip3] triton==3.5.0
[conda] Could not collect
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.12.0
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
GPU0 GPU1 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PIX 0-15 0 N/A
GPU1 PIX X 0-15 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>=12.9 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 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
NVIDIA_DRIVER_CAPABILITIES=compute,utility
VLLM_USAGE_SOURCE=production-docker-image
CUDA_VERSION=12.9.1
LD_LIBRARY_PATH=/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/lib64
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
For more details here the error log:
(APIServer pid=1382) INFO 12-16 01:31:53 [api_server.py:1772] vLLM API server version 0.12.0
(APIServer pid=1382) INFO 12-16 01:31:53 [utils.py:253] non-default args: {'model_tag': '/vllm-workspace/models/Olmo-3-32B-Think-GGUF/Olmo-3-32B-Think-Q4_0.gguf', 'host': '0.0.0.0', 'port': 8001, 'model': '/vllm-workspace/models/Olmo-3-32B-Think-GGUF/Olmo-3-32B-Think-Q4_0.gguf', 'max_model_len': 32768, 'served_model_name': ['Olmo-3.1-Thinking'], 'tensor_parallel_size': 2, 'gpu_memory_utilization': 0.6}
(APIServer pid=1382) Traceback (most recent call last):
(APIServer pid=1382) File "/usr/local/bin/vllm", line 10, in <module>
(APIServer pid=1382) sys.exit(main())
(APIServer pid=1382) ^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/main.py", line 73, in main
(APIServer pid=1382) args.dispatch_function(args)
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/cli/serve.py", line 60, in cmd
(APIServer pid=1382) uvloop.run(run_server(args))
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 96, in run
(APIServer pid=1382) return __asyncio.run(
(APIServer pid=1382) ^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/lib/python3.12/asyncio/runners.py", line 195, in run
(APIServer pid=1382) return runner.run(main)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
(APIServer pid=1382) return self._loop.run_until_complete(task)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 48, in wrapper
(APIServer pid=1382) return await main
(APIServer pid=1382) ^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 1819, in run_server
(APIServer pid=1382) await run_server_worker(listen_address, sock, args, **uvicorn_kwargs)
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 1838, in run_server_worker
(APIServer pid=1382) async with build_async_engine_client(
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1382) return await anext(self.gen)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 183, in build_async_engine_client
(APIServer pid=1382) async with build_async_engine_client_from_engine_args(
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
(APIServer pid=1382) return await anext(self.gen)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 209, in build_async_engine_client_from_engine_args
(APIServer pid=1382) vllm_config = engine_args.create_engine_config(usage_context=usage_context)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/engine/arg_utils.py", line 1356, in create_engine_config
(APIServer pid=1382) maybe_override_with_speculators(
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/vllm/transformers_utils/config.py", line 477, in maybe_override_with_speculators
(APIServer pid=1382) config_dict, _ = PretrainedConfig.get_config_dict(
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py", line 662, in get_config_dict
(APIServer pid=1382) config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/transformers/configuration_utils.py", line 753, in _get_config_dict
(APIServer pid=1382) config_dict = load_gguf_checkpoint(resolved_config_file, return_tensors=False)["config"]
(APIServer pid=1382) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(APIServer pid=1382) File "/usr/local/lib/python3.12/dist-packages/transformers/modeling_gguf_pytorch_utils.py", line 431, in load_gguf_checkpoint
(APIServer pid=1382) raise ValueError(f"GGUF model with architecture {architecture} is not supported yet.")
(APIServer pid=1382) ValueError: GGUF model with architecture olmo2 is not supported yet.
🐛 Describe the bug
I am trying to deploy Olmo3 thinking 32B GGUF using vllm serve but I keep getting following error: ValueError: GGUF model with architecture olmo2 is not supported yet.
Is there anything I can do to fix this?
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