---
library_name: transformers
datasets:
- agibot-world/AgiBotWorld-Beta
- agibot-world/AgiBotWorld-Alpha

---



# GO-1

<!-- Provide a quick summary of what the model is/does. -->

GO-1 is our robotic foundation model pretrained on [AgiBot World Dataset](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Beta).

Please refer to our [project page](https://agibot-world.com/), [github repo](https://github.com/OpenDriveLab/Agibot-World) and [paper](https://arxiv.org/abs/2503.06669) for more details.

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

- **Developed by:** Team AgiBot-World
- **Model type:** Vision-Language-Action model
- **License:** CC BY-NC-SA 4.0
- **Vision Language Model:** [InternVL 2.5-2B](https://huggingface.co/OpenGVLab/InternVL2_5-2B)
- **Pre-training Dataset:** [AgiBot World Dataset](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Beta)

### Model Sources

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/OpenDriveLab/Agibot-World
- **Paper:** https://arxiv.org/abs/2503.06669
- **Project Page:** https://agibot-world.com/

## Uses

This is the pre-trained GO-1 model. For fine-tuning on simulation benchmarks or your customized dataset, please visit our [github repo](https://github.com/OpenDriveLab/Agibot-World).

## Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

- Please consider citing our work if it helps your research.
- For the full authorship and detailed contributions, please refer to [contributions](https://github.com/OpenDriveLab/AgiBot-World/blob/main/CONTRIBUTING.md).
- In alphabetical order by surname:

```BibTeX
@article{bu2025agibot,
  title={Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems},
  author={Bu, Qingwen and Cai, Jisong and Chen, Li and Cui, Xiuqi and Ding, Yan and Feng, Siyuan and Gao, Shenyuan and He, Xindong and Huang, Xu and Jiang, Shu and others},
  journal={arXiv preprint arXiv:2503.06669},
  year={2025}
}

@inproceedings{bu2025agibot,
  title={Agibot world colosseo: A large-scale manipulation platform for scalable and intelligent embodied systems},
  author={Bu, Qingwen and Cai, Jisong and Chen, Li and Cui, Xiuqi and Ding, Yan and Feng, Siyuan and He, Xindong and Huang, Xu and others},
  booktitle={2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2025},
  organization={IEEE}
}
```