Qwen2-VL: Enhancing Vision-Language Model's

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