---
pipeline_tag: image-to-video
base_model: nvidia/Cosmos-Predict2.5-2B
tags:
- World-Model
- Multi-Agent
---

# **Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players**

[**Code**](https://github.com/nv-tlabs/Gamma-World) | [**Paper**](https://huggingface.co/papers/2605.28816) | [**Website**](https://research.nvidia.com/labs/sil/projects/gamma-world/)

Gamma-World (γ-World) is a generative multi-agent world model that renders a single shared world in which several independently-controlled agents stay causally connected. It supports action-responsive streaming rollouts and generalizes from two-player training to four-player (and beyond) interaction without additional training. Gamma-World is built on the NVIDIA Cosmos stack ([Cosmos-Predict2.5](https://github.com/nvidia-cosmos/cosmos-predict2.5)).

## Citation

```bibtex
@article{gammaworld2026,
    title={Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players},
    author={Fangfu Liu and Kai He and Tianchang Shen and Tianshi Cao and
            Sanja Fidler and Yueqi Duan and Jun Gao and Igor Gilitschenski and
            Zian Wang and Xuanchi Ren},
    journal={arXiv preprint arXiv:2605.28816},
    year={2026}
}
```