ByteDance-Seed / UI-TARS-1.5-7B

UI-TARS-1.5 Model

Introduction

UI-TARS-1.5, an open-source multimodal agent built upon a powerful vision-language model. It is capable of effectively performing diverse tasks within virtual worlds.

Leveraging the foundational architecture introduced in our recent paper , UI-TARS-1.5 integrates advanced reasoning enabled by reinforcement learning. This allows the model to reason through its thoughts before taking action, significantly enhancing its performance and adaptability, particularly in inference-time scaling. Our new 1.5 version achieves state-of-the-art results across a variety of standard benchmarks, demonstrating strong reasoning capabilities and notable improvements over prior models.

Code: https://github.com/bytedance/UI-TARS

Application: https://github.com/bytedance/UI-TARS-desktop

Performance

Online Benchmark Evaluation

Grounding Capability Evaluation

Poki Game

Minecraft

Model Scale Comparison

This table compares performance across different model scales of UI-TARS on the OSworld benchmark.

Citation

If you find our paper and model useful in your research, feel free to give us a cite.

@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}
}