Qwen2 VL 72B is a multimodal LLM from the Qwen Team with the following key enhancements: - 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. For more details, see thisblog postandGitHub repo. Usage of this model is subject toTongyi Qianwen LICENSE AGREEMENT.
Comments
No comments yet. Be the first to comment!
Related Tools
Qwen2.5 72B Instruct
huggingface.co/Qwen
Qwen2.5 72B is the latest series of Qwen large language models.
Qwen2.5-72B
qwenlm.github.io
Alibaba's flagship LLM pre-trained on 18 trillion tokens, matching Llama-3-405B performance (5x smaller), excelling in knowledge, reasoning, math, and coding benchmarks.
GLM-4.7
www.bigmodel.cn
An open-source multilingual multimodal chat model from Zhipu AI with advanced thinking capabilities, exceptional coding performance, and enhanced UI generation.
Related Insights
Stop Cramming AI Assistants into Chat Boxes: Clawdbot Picked the Wrong Battlefield
Clawdbot is convenient, but putting it inside Slack or Discord was the wrong design choice from day one. Chat tools are not for operating tasks, and AI isn't for chatting.
The Twilight of Low-Code Platforms: Why Claude Agent SDK Will Make Dify History
A deep dive from first principles of large language models on why Claude Agent SDK will replace Dify. Exploring why describing processes in natural language is more aligned with human primitive behavior patterns, and why this is the inevitable choice in the AI era.

Anthropic Subagent: The Multi-Agent Architecture Revolution
Deep dive into Anthropic multi-agent architecture design. Learn how Subagents break through context window limitations, achieve 90% performance improvements, and real-world applications in Claude Code.