nv-tlabs/lyra

Project Lyra: Open Generative 3D World Models

Python

2,322

21 commits

updated Jul 20, 2026

See the code

README

Project Lyra: Open Generative 3D World Models

NVIDIA Spatial Intelligence Lab

https://github.com/user-attachments/assets/f47c24c0-453e-4134-84f1-80c56613f4af

🫨 News

  • 2026-07-20: 👋 We released the Lyra-2.0 GUI and training code — see the GUI instructions and training instructions.
  • 2026-04-15: 👋 We released Lyra-2.0. Explorable generative 3D worlds with long-horizon, 3D-consistent generation.
  • 2025-09-23: 👋 We released Lyra-1.0. Feed-forward 3D and 4D scene generation from a single image/video via video diffusion model self-distillation.

📝 Overview

Project Lyra is a series of open generative 3D world models developed at NVIDIA.

This repository provides the official implementations of Lyra 1.0 and Lyra 2.0.

Version📄 Paper🌐 Project Page🤗 Model💻 Code
Lyra 1.0arXivPageHuggingFaceCode
Lyra 2.0arXivPageHuggingFaceCode

License

Lyra source code is released under the Apache 2.0 License. Please refer to Lyra-1 and Lyra-2 for their respective model licenses.

Citation

If you find our series of models or the report helpful to your research or applications, please consider citing our paper.

@inproceedings{bahmani2026lyra,
  title={Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation},
  author={Bahmani, Sherwin and Shen, Tianchang and Ren, Jiawei and Huang, Jiahui and Jiang, Yifeng and 
          Turki, Haithem and Tagliasacchi, Andrea and Lindell, David B. and Gojcic, Zan and Fidler, Sanja and 
          Ling, Huan and Gao, Jun and Ren, Xuanchi},
  booktitle={International Conference on Learning Representations (ICLR)},
  year={2026}
}
@article{shen2026lyra2,
    title={Lyra 2.0: Explorable Generative 3D Worlds},
    author={Shen, Tianchang and Bahmani, Sherwin and He, Kai and Srinivasan, Sangeetha Grama and Cao, Tianshi and Ren, Jiawei and Li, Ruilong and Wang, Zian and Sharp, Nicholas and Gojcic, Zan and Fidler, Sanja and Huang, Jiahui and Ling, Huan and Gao, Jun and Ren, Xuanchi},
    journal={arXiv preprint arXiv:2604.13036},
    year={2026}
}
3d
diffusion
gaussians
video
world-model

Significant stargazers

Matt Stancliff

625 followers · starred Dec 2025

Ilya Kirillov

91 followers · starred Apr 2026

Ryan C. Hill

72 followers · starred Feb 2026

Ryohei Sasaki

696 followers · starred Oct 2025

nv-tlabs/lyra

Project Lyra: Open Generative 3D World Models

Python

2,322

21 commits

updated Jul 20, 2026

See the code

README

Project Lyra: Open Generative 3D World Models

NVIDIA Spatial Intelligence Lab

https://github.com/user-attachments/assets/f47c24c0-453e-4134-84f1-80c56613f4af

🫨 News

  • 2026-07-20: 👋 We released the Lyra-2.0 GUI and training code — see the GUI instructions and training instructions.
  • 2026-04-15: 👋 We released Lyra-2.0. Explorable generative 3D worlds with long-horizon, 3D-consistent generation.
  • 2025-09-23: 👋 We released Lyra-1.0. Feed-forward 3D and 4D scene generation from a single image/video via video diffusion model self-distillation.

📝 Overview

Project Lyra is a series of open generative 3D world models developed at NVIDIA.

This repository provides the official implementations of Lyra 1.0 and Lyra 2.0.

Version📄 Paper🌐 Project Page🤗 Model💻 Code
Lyra 1.0arXivPageHuggingFaceCode
Lyra 2.0arXivPageHuggingFaceCode

License

Lyra source code is released under the Apache 2.0 License. Please refer to Lyra-1 and Lyra-2 for their respective model licenses.

Citation

If you find our series of models or the report helpful to your research or applications, please consider citing our paper.

@inproceedings{bahmani2026lyra,
  title={Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation},
  author={Bahmani, Sherwin and Shen, Tianchang and Ren, Jiawei and Huang, Jiahui and Jiang, Yifeng and 
          Turki, Haithem and Tagliasacchi, Andrea and Lindell, David B. and Gojcic, Zan and Fidler, Sanja and 
          Ling, Huan and Gao, Jun and Ren, Xuanchi},
  booktitle={International Conference on Learning Representations (ICLR)},
  year={2026}
}
@article{shen2026lyra2,
    title={Lyra 2.0: Explorable Generative 3D Worlds},
    author={Shen, Tianchang and Bahmani, Sherwin and He, Kai and Srinivasan, Sangeetha Grama and Cao, Tianshi and Ren, Jiawei and Li, Ruilong and Wang, Zian and Sharp, Nicholas and Gojcic, Zan and Fidler, Sanja and Huang, Jiahui and Ling, Huan and Gao, Jun and Ren, Xuanchi},
    journal={arXiv preprint arXiv:2604.13036},
    year={2026}
}
3d
diffusion
gaussians
video
world-model

Significant stargazers

Matt Stancliff

625 followers · starred Dec 2025

Ilya Kirillov

91 followers · starred Apr 2026

Ryan C. Hill

72 followers · starred Feb 2026

Ryohei Sasaki

696 followers · starred Oct 2025

Languages

Python

65.4%

C++

22.8%

C

6.2%

Cuda

5.0%