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LLMs ·

Qwen3-VL 235B-A22B Instruct

Parameters
236B (22.0B active)
Architecture
Mixture of experts
Max context
256K tokens
License
apache-2.0
Released
2025-09

How to run it

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run qwen3-vl:235b

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen3-VL-235B-A22B-Instruct-GGUF

Original weights · Hugging Face

Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.

huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct (opens in a new tab)

No sign-in needed.

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

Memory needed

Weights plus KV cache and runtime overhead. Leave a little extra free for the operating system and other apps.

Quantization Quality Weights Total at 8K context Total at 32K context Download
Q2_K Low 94.3 GB 96.4 GB 101 GB GGUF files (opens in a new tab)
Q3_K_M Low 115 GB 118 GB 122 GB GGUF files (opens in a new tab)
Q4_K_M Good 144 GB 146 GB 151 GB GGUF · part 1 of 3 (opens in a new tab)
Q5_K_M High 167 GB 170 GB 174 GB GGUF files (opens in a new tab)
Q6_K High 193 GB 195 GB 200 GB GGUF files (opens in a new tab)
Q8_0 Very high 250 GB 252 GB 257 GB GGUF · part 1 of 6 (opens in a new tab)
F16 Full 471 GB 474 GB 478 GB GGUF · part 1 of 10 (opens in a new tab) Original weights (opens in a new tab)

Best hardware for Qwen3-VL 235B-A22B Instruct

Grade · points Hardware Quant Memory Speed Fit
88 ptsExcellent (S) · 88 of 100 points: Model quality 38.0/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 15.0/15 Apple M3 Ultra (256 GB) Q4_K_M 161 GB / 192 GB 19.7 tok/s Runs well
84 ptsGreat (A) · 84 of 100 points: Model quality 33.6/45, Memory fit 24.0/25, Speed 11.8/15, Memory use 15.0/15 Apple M2 Ultra (192 GB) Q3_K_M 129 GB / 144 GB 24.8 tok/s Tight fit
84 ptsGreat (A) · 84 of 100 points: Model quality 38.0/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 10.6/15 Apple M3 Ultra (512 GB) Q4_K_M 177 GB / 384 GB 19.7 tok/s Runs well
75 ptsGreat (A) · 75 of 100 points: Model quality 28.0/45, Memory fit 24.0/25, Speed 8.4/15, Memory use 15.0/15 NVIDIA GB10 (128 GB) Q2_K 106 GB / 115 GB 12.5 tok/s Tight fit
66 ptsGood (B) · 66 of 100 points: Model quality 28.0/45, Memory fit 10.0/25, Speed 13.8/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell Q2_K 101 GB / 96.0 GB 33.7 tok/s Runs with offload
63 ptsGood (B) · 63 of 100 points: Model quality 28.0/45, Memory fit 10.0/25, Speed 10.1/15, Memory use 15.0/15 Apple M4 Max (128 GB) Q2_K 104 GB / 96.0 GB 18.3 tok/s Runs with offload
59 ptsGood (B) · 59 of 100 points: Model quality 28.0/45, Memory fit 10.0/25, Speed 6.9/15, Memory use 15.0/15 AMD Ryzen AI Max+ 395 (128 GB) Q2_K 104 GB / 96.0 GB 8.6 tok/s Runs with offload

Check it on your own hardware

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.