Qwen3-VL-32B
Qwen3-VL-32B is an open-weights language model from Qwen, released October 21, 2025. It has 33B parameters (dense). The context window is 256K 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-32B locally?
The smallest common GPU it runs on is 16 GB of VRAM (with 32 GB of RAM): IQ3_XXS, split GPU / CPU, roughly 8 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 | Very slow | IQ3_XXS (noticeable loss) | 5.2 GB | 12.5 GB | ~2 |
| 8 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 7.2 GB | 10.5 GB | ~3 |
| 12 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 11.2 GB | 6.5 GB | ~4 |
| 16 GB VRAM | Runs, slowly | IQ3_XXS (noticeable loss) | 15.2 GB | 2.5 GB | ~8 |
| 24 GB VRAM | Runs on GPU | IQ4_XS (good) | 22.6 GB | – | ~31 |
| 32 GB VRAM | Runs on GPU | Q5_K_M (excellent) | 28.6 GB | – | ~43 |
Ready-made quantizations on Hugging Face: Qwen/Qwen3-VL-32B-Instruct-GGUF · pottokao/MiniMax-H3-TextEncoder-Qwen3VL-32B-abliterated-GGUF · pottokao/MiniMax-H3-TextEncoder-16GB-abliterated-GGUF · unsloth/Qwen3-VL-32B-Instruct-GGUF · pottokao/MiniMax-H3-TextEncoder-16GB-GGUF · bartowski/Qwen_Qwen3-VL-32B-Instruct-GGUF
Benchmark results
Epoch AI has not published results for Qwen3-VL-32B yet. New models are usually evaluated within days to weeks.
Links
Announcement · Hugging Face: Qwen/Qwen3-VL-32B-Instruct
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