Qwen2-VL is the latest version of the vision language models based on Qwen2 in the Qwen model familities. The latest version of the visual language model released by AliCloud is a significant improvement over its predecessor, Qwen-VL.Qwen2-VL features advanced comprehension of multi-resolution and scaled images and excels in several visual comprehension benchmarks, including MathVista, DocVQA, RealWorldQA, and MTVQA.
Key Features
- SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc.
- Understanding videos of 20min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc.
- Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions.
- Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc.
Application Scenarios
- Content creation: Qwen2-VL automatically generates descriptions of video and image content, helping creators to quickly produce multimedia works.
- Educational assistance: As an educational tool, Qwen2-VL helps students parse math problems and logic diagrams, providing guidance on problem-solving.
- Multilingual Translation and Understanding: Qwen2-VL recognizes and translates multilingual text, facilitating cross-lingual communication and content understanding.
- Intelligent Customer Service: Integrated with real-time chat functionality, Qwen2-VL provides instant customer counseling services.
- Image and Video Analytics: In security monitoring and social media management, Qwen2-VL analyzes visual content and identifies critical information.
- Assisted Design: Designers use Qwen2-VL’s image comprehension capabilities for design inspiration and conceptual drawings.
- Automated Testing: Qwen2-VL automates the detection of interface and functionality issues in software development.
- Data Retrieval and Information Management: Qwen2-VL improves the automation of information retrieval and management through visual agent capabilities.
- Assisted Driving and Robot Navigation: Qwen2-VL acts as a visual perception component to assist autonomous driving and robots in understanding their environment.
- Medical Image Analysis: Qwen2-VL assists medical professionals in analyzing medical images to improve diagnostic efficiency.
Related information
- Official Description: https://qwenlm.github.io/blog/qwen2-vl/
- GitHub: https://github.com/QwenLM/Qwen2-VL
- Model Download: https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d
- Online demo: https://huggingface.co/spaces/Qwen/Qwen2-VL
- API: https://help.aliyun.com/zh/model-studio/developer-reference/qwen-vl-api