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Decision brief
Qwen-VL by Alibaba Cloud is a large vision-language model suitable for tasks blending image understanding with NLP, available under flexible licensing.
Good fit when
- When needing to integrate visual inputs with natural language in AI applications
- For tasks requiring state-of-the-art performance in vision-language modeling
Avoid when
- If the application requires only traditional computer vision without language integration
- In scenarios where Python 3.8 or newer and PyTorch 1.12+ are not feasible for installation
- Requirements:
- Requires python >=3.8, pytorch>=1.12 (cuda >=11.4 recommended)
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (740d since push)
- As of 3d
- Provenance
- Not a fork · Organization account
- As of 3d
- Security (OSV)
- 44 low (44 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Qwen-VLHow it fits your stack(6)
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Qwen-VL (通义千问-VL) is a chat and pretrained large vision-language model proposed by Alibaba Cloud, designed for integrating vision and natural language processing tasks. Repository includes both the base Qwen-VL model and its chat variant.
Capability facts
- Languages
- python
Source: github.language · Aug 17, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 17, 2026)
* python 3.8 and aboveSource link
Tags
README
Requirements
- python 3.8 and above
- pytorch 1.12 and above, 2.0 and above are recommended
- CUDA 11.4 and above are recommended (this is for GPU users)
License Agreement
Researchers and developers are free to use the codes and model weights of both Qwen-VL and Qwen-VL-Chat. We also allow their commercial use. Check our license at LICENSE for more details.
For agents
This page has a .md twin and JSON over the API.