Qwen3-VL 235B-A22B
Qwen3-VL 235B-A22B is an open-weights language model from Qwen, released April 1, 2025. It has 236B parameters (mixture-of-experts, 22B active). The context window is 128K tokens. API price: $0.7 input / $2.8 output per million tokens.
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively supports interleaved contexts of up to 256K tokens, seamlessly integrating text, images, and video.
Check it against your own PC →
Can you run Qwen3-VL 235B-A22B locally?
The smallest common GPU it runs on is 32 GB of VRAM (with 32 GB of RAM): IQ1_M, GPU + experts in RAM, roughly 19 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Too large | – | – | – | – |
| 8 GB VRAM | Too large | – | – | – | – |
| 12 GB VRAM | Too large | – | – | – | – |
| 16 GB VRAM | Too large | – | – | – | – |
| 24 GB VRAM | Too large | – | – | – | – |
| 32 GB VRAM | Runs · GPU + CPU experts | IQ1_M (experimental) | 31.2 GB | 24.1 GB | ~19 |
Ready-made quantizations on Hugging Face: unsloth/Qwen3-VL-235B-A22B-Instruct-GGUF · Qwen/Qwen3-VL-235B-A22B-Instruct-GGUF · unsloth/Qwen3-VL-235B-A22B-Instruct-1M-GGUF · DevQuasar/Qwen.Qwen3-VL-235B-A22B-Instruct-GGUF · lmstudio-community/Qwen3-VL-235B-A22B-Instruct-GGUF · noctrex/Qwen3-VL-235B-A22B-Instruct-1M-MXFP4_MOE-GGUF
Benchmark results
Epoch AI has not published results for Qwen3-VL 235B-A22B yet. New models are usually evaluated within days to weeks.
Links
Announcement · Hugging Face: Qwen/Qwen3-VL-235B-A22B-Instruct
More from Qwen
Qwen3.8 Omni Flash · Qwen3.8 Max (0902) · Qwen3.8 Flash · Qwen3.8 Flash Next · Qwen 3.8 27B · Qwen3.8-2.4T-A95B · Qwen 3.8 Max · Qwen3.7 Flash