Qwen-VL

Alibaba's 2023 vision-language model, now unmaintained and replaced by Qwen2.5-VL and Qwen3-VL.

Open SourceSelf HostedOffline CapableGPU Required (8GB+ VRAM)
0.0 (0)

About

Alibaba Cloud's first open vision-language model arrived in August 2023 as Qwen-VL and its dialogue-tuned sibling Qwen-VL-Chat, pairing the Qwen-7B language model with a large ViT image encoder fed 448 by 448 pixel inputs. That resolution, plus training aimed at reading text and returning bounding boxes, made it unusually good with documents, charts and grounding questions for its time, and an Int4 build lowered the memory bar. The last commit to the repository was in April 2024, and the model line has since moved on through Qwen2-VL, Qwen2.5-VL and Qwen3-VL. The original weights still load from Hugging Face, but only with trust_remote_code and an old Transformers release, since the repo pins version 4.32.0, which makes it awkward inside current serving stacks. Mind the license: weights and code use the Tongyi Qianwen License Agreement rather than Apache-2.0; it permits commercial use below 100 million monthly active users and forbids using outputs to improve other LLMs. For new work, choose Qwen3-VL, which is Apache-2.0, or Qwen2.5-VL, checking the license of the specific size you pick.

Should you use Qwen-VL?

Pick it when

Pick this when you need an Apache-2.0 vision-language model for OCR, captioning, and grounding with a chat variant on an 8 GB-class GPU, and want hosted Qwen-VL-Plus or Max tiers as an upgrade path.

Look elsewhere when

Skip it if you want a current-generation model: the original Qwen-VL line has been superseded, and Qwen3.8's Apache-2.0 27B adds video. For heavy document parsing, InternVL 2.5 or a dedicated OCR model like olmOCR fits better.

Alternatives to Qwen-VL

  • Qwen3.8

    Newer Alibaba Apache-2.0 27B that reads images and video, at a larger footprint of about 17 GB at 4-bit.

  • InternVL 2.5

    MIT licensed with strong OCR, chart, and table results across several sizes, a better fit for document understanding.

  • Pixtral

    Apache-2.0 12B with 128K context for long multi-image conversations, at a larger 12 GB-class footprint.

  • olmOCR

    Purpose-built document OCR toolkit from AI2, the better pick when the job is converting PDFs to text rather than visual chat.

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Details

Price
Free
Platform
Local/Desktop
Difficulty
Intermediate (3/5)
License
Tongyi Qianwen License Agreement
Minimum VRAM
8 GB
Added
Apr 3, 2026

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