WorldCast

WorldCast: Distributed Multiplayer World Models

Ziyang Ye¹, Junchao Huang^1,2, Evelyn Zhang², Zhihao Xie¹, Ruicheng Zhang³, Boyao Han¹, Litao Ban⁴, Ziye Wang⁴, Xinting Hu⁵, Shaoshuai Shi⁴, Zhuotao Tian², Li Jiang^1,2†

¹CUHK-Shenzhen  ²SLAI  ³Tsinghua SIGS  ⁴Voyager Research, Didi Chuxing  ⁵USTC  ^†Corresponding author

Project page | Code | Paper (coming soon)

WorldCast is a distributed multiplayer world model. Each player runs a local client, a video generator fine-tuned from Wan2.2-TI2V-5B, on its own GPU. Clients exchange only player states, which each client projects into a camera-aligned player state field, and a shared scene state of generated blocks. This repository holds the weights of the release: the final 4-step model first, with everything the inference code loads beside it.

Files

The generator file holds EMA weights under the parameter names of the release model (WorldCastGenerator), so a strict load_state_dict works. The inference code needs the five weight files above and nothing else of this repository.

Training checkpoints

EMA weights of the training stages, fp32, under the same names as the generator file; training from them starts from the exact weights. They also hold the visibility probe the training uses (8 tensors).

The stage 2 checkpoint and the training code are added to this repository next.

Quick start

git clone https://github.com/Ziyang-Ye/WorldCast && cd WorldCast
pip install -e .
python tools/download_weights.py --out-dir weights

This fetches the inference files above, plus the Wan2.2 VAE, tokenizer and config.json from Wan-AI/Wan2.2-TI2V-5B, and writes weights/paths.yaml. Running a session, the examples and the demo, and the options of the download: see the code repository.

License and attribution

• The WorldCast weights are released under the Apache License 2.0.
• They are fine-tuned from Wan2.2-TI2V-5B (Apache License 2.0).
• Training data: the OpenCS2 dataset (CC BY 4.0). The files under examples/ are derived from it.
• The model renders Counter-Strike 2 game content and is intended for research. Counter-Strike 2 is a trademark of Valve Corporation; this work is not affiliated with or endorsed by Valve.

Citation

@article{ye2026worldcast,
  title   = {WorldCast: Distributed Multiplayer World Models},
  author  = {Ye, Ziyang and Huang, Junchao and Zhang, Evelyn and Xie, Zhihao and Zhang, Ruicheng and Han, Boyao and Ban, Litao and Wang, Ziye and Hu, Xinting and Shi, Shaoshuai and Tian, Zhuotao and Jiang, Li},
  journal = {arXiv preprint},
  year    = {2026}
}