Field noteOct 26, 20261 min read1 source

Qwen released a 4-bit AWQ quantization of their 3B vision-language model, over 800K downloads.

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Qwen has published Qwen2.5-VL-3B-Instruct-AWQ on Hugging Face, a 4-bit AWQ quantization of its Qwen2.5-VL-3B-Instruct vision-language model.

What changed: A separate Qwen2.5-VL-3B-Instruct AWQ release adds vision-language capability and has surpassed 800K downloads; the prior covers the text-only Qwen2.5-3B-Instruct AWQ build.

The public repository is not gated and is tagged for image-text-to-text use, multimodal conversations, Transformers, Safetensors, and 4-bit AWQ.

The repository lists 3,754,622,976 total parameters and a total Safetensors file size of 3,401,785,760 bytes. At the time reflected in the supplied source, it showed 823,683 downloads for the period tracked by Hugging Face and 3,948,118 downloads all time. The model card includes loading examples with Transformers and serving instructions for vLLM, including an OpenAI-compatible chat-completions endpoint.

The source identifies the base model and quantization format, but does not provide benchmark comparisons, memory requirements, throughput measurements, quality-loss measurements versus the original model, or a supported-hardware matrix. It also does not establish how the tracked download count maps to active deployments.

Evidence / sources

  1. 1huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct-AWQ
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