[!IMPORTANT]

[2025-03-18] We released a technical preview version of a new desktop app - Agent TARS, a multimodal AI agent that leverages browser operations by visually interpreting web pages and seamlessly integrating with command lines and file systems.

UI-TARS Desktop

UI-TARS Desktop is a GUI Agent application based on UI-TARS (Vision-Language Model) that allows you to control your computer using natural language.

Showcases

| Instruction | Video | | :---: | :---: | | Please help me open the autosave feature of VS Code and delay AutoSave operations for 500 milliseconds in the VS Code setting. | | | Could you help me check the latest open issue of the UI-TARS-Desktop project on GitHub? | |

News

• [2025-04-17] - 🎉 We're thrilled to announce the release of new UI-TARS Desktop application v0.1.0, featuring a redesigned Agent UI. The application enhances the computer using experience, introduces new browser operation features, and supports the advanced UI-TARS-1.5 model for improved performance and precise control.
• [2025-02-20] - 📦 Introduced UI TARS SDK, is a powerful cross-platform toolkit for building GUI automation agents.
• [2025-01-23] - 🚀 We updated the Cloud Deployment section in the 中文版: GUI模型部署教程 with new information related to the ModelScope platform. You can now use the ModelScope platform for deployment.

Features

• 🤖 Natural language control powered by Vision-Language Model
• 🖥️ Screenshot and visual recognition support
• 🎯 Precise mouse and keyboard control
• 💻 Cross-platform support (Windows/MacOS/Browser)
• 🔄 Real-time feedback and status display
• 🔐 Private and secure - fully local processing

Quick Start

See Quick Start.

Deployment

See Deployment.

Contributing

See CONTRIBUTING.md.

SDK (Experimental)

See @ui-tars/sdk

License

UI-TARS Desktop is licensed under the Apache License 2.0.

Citation

If you find our paper and code useful in your research, please consider giving a star :star: and citation :pencil:

@article{qin2025ui,
  title={UI-TARS: Pioneering Automated GUI Interaction with Native Agents},
  author={Qin, Yujia and Ye, Yining and Fang, Junjie and Wang, Haoming and Liang, Shihao and Tian, Shizuo and Zhang, Junda and Li, Jiahao and Li, Yunxin and Huang, Shijue and others},
  journal={arXiv preprint arXiv:2501.12326},
  year={2025}
}