---
dataset_name: Magic-RICH
pretty_name: Magic-RICH (Mobile GUI Agent Benchmark, CN)
tags:
  - gui
  - mobile
  - android
  - visual-grounding
  - vqa
  - agent
  - chinese
task_categories:
  - other
language:
  - en
license: apache-2.0
size_categories:
  - 1K<n<10K
homepage: https://github.com/OpenBMB/AgentCPM-GUI
paper: https://arxiv.org/abs/2508.03700
repository: https://huggingface.co/datasets/GUIAgent/Magic-RICH
---

# Dataset Summary
Magic-RICH is a Chinese benchmark dataset for evaluating mobile GUI agents in realistic smartphone environments. It contains 4,000 step-level samples across four subsets, covering 17 categories and over 150 popular apps. Unlike many previous GUI datasets, Magic-RICH also includes special actions such as screenshot and long screenshot to better reflect real-world interactions. This dataset is designed for evaluation only (no train/dev split) and was used in the development of MagicGUI, an open-source GUI agent.

# Subsets
Magic-RICH is composed of four balanced subsets (1,000 samples each):

- Routine: High-frequency, single-step actions (e.g., tap, scroll, text input).  
- Instruction: Direct user commands (e.g., "Open...", "Check membership"), testing instruction-to-action mapping.  
- Complex: Harder tasks requiring reasoning (logical conditions, visual analysis, multi-step navigation).  
- Handling Exception: Special cases including  
  - *Non-interactive* (page cannot be acted on),  
  - *Completed* (task already finished),  
  - *Loading* (page still in transition). 

# Evaluation Protocol
Three metrics are recommended for evaluation:  
- Type – action type accuracy (e.g., Tap vs. Scroll)  
- Grd – grounding accuracy (tap/scroll location falls inside ground-truth element box)  
- SR – full correctness at the step level (all parameters correct)  

# License
This project is licensed under the [Apache-2.0](./LICENSE) license. The model weights are fully open for academic research, and commercial use licenses can be applied for by contacting magicgui@honor.com. This project uses the pre-trained Qwen2VL-7B-Instruct for initialization, which is also licensed under the Apache- 2.0 License.

# Citation
If you use Magic-RICH in your research, please cite:

```bibtex
@misc{tang2025magicguifoundationalmobilegui,
      title={MagicGUI: A Foundational Mobile GUI Agent with Scalable Data Pipeline and Reinforcement Fine-tuning}, 
      author={Liujian Tang and Shaokang Dong and Yijia Huang and Minqi Xiang and Hongtao Ruan and Bin Wang and Shuo Li and Zhiheng Xi and Zhihui Cao and Hailiang Pang and Heng Kong and He Yang and Mingxu Chai and Zhilin Gao and Xingyu Liu and Yingnan Fu and Jiaming Liu and Xuanjing Huang and Yu-Gang Jiang and Tao Gui and Qi Zhang and Kang Wang and Yunke Zhang and Yuran Wang},
      year={2025},
      eprint={2508.03700},
      archivePrefix={arXiv},
      primaryClass={cs.HC},
      url={https://arxiv.org/abs/2508.03700}, 
}