Overview
Qwen3-VL is the latest vision-language model series released by the Qwen team at Alibaba Cloud. It delivers improvements in visual reasoning, spatial perception, and long-context handling for documents and videos. The repository provides code, cookbooks, demos and deployment examples compatible with Transformers and vLLM.
Key features
- Strong visual-language reasoning across document parsing, object recognition and scene understanding.
- Native long context (256K tokens) with support for expansion to 1M tokens for long documents and videos.
- Enhanced video understanding and text-timestamp alignment for video QA and retrieval.
- Available in Dense and MoE architectures, with Instruct and Thinking variants.
- Cookbooks, example code, and inference recipes for vLLM/Transformers, plus deployment guides.
Use cases
- Document and receipt parsing with spatial layout awareness.
- Multimodal QA and retrieval (image+text, video+text).
- Vision-powered automation agents (mobile and desktop GUIs).
- Video understanding, key information extraction, scene segmentation and temporal event localization.
Technical details
- Interleaved-MRoPE and DeepStack position encoding and multi-scale visual fusion for improved long-context and video performance.
- Compatible with Transformers and vLLM; supports FP8/quantization and acceleration techniques such as Flash-Attention 2.
- Deployment examples include vLLM, SGLang and Docker images with recommended optimizations.