---
license: cc-by-nc-4.0
---

<p align="center">
    <img src="assets/oxtal-logo.png" alt="OXtal: Generative Molecular Crystal Structure Prediction" width="900"/><br>
  <a href="https://arxiv.org/abs/2512.06987"><img src="https://img.shields.io/badge/arXiv-94133F?style=for-the-badge&logo=arxiv" alt="arXiv"/></a>
  <a href="https://oxtal.github.io/"><img src="https://img.shields.io/badge/📝%20Blog-007A87?style=for-the-badge&logoColor=white" alt="Blog"/></a>
  <a href="https://github.com/OXtal/OXtal"><img src="https://img.shields.io/badge/GitHub-747474.svg?style=for-the-badge&logo=GitHub&logoColor=white" alt="HF"/></a>
</p>

**OX**tal (**O**rganic **X** "Crys-" tal) is an all-atom diffusion model for molecular crystal structure prediction (CSP). 
Unlike traditional quantum-chemical approaches, which rely on expensive energy oracles, OXtal generates fast and accurate zero-shot 
predictions at a fraction of the cost. Specifically, OXtal recovers experimental crystal structures for both rigid and flexible molecules, 
as well as co-crystals, with conformer RMSD1 < 0.5 Å and attains over 80% packing similarity rate, demonstrating its ability to model 
both thermodynamic and kinetic regularities of molecular crystallization.

The model was introduced in the paper, [OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction](https://arxiv.org/abs/2512.06987) (ICLR 2026).

## 🚀 Sample Usage

To run inference, please follow the installation instructions in the [official GitHub repository](https://github.com/OXtal/OXtal).
You can then run generation using the provided runner:

```
# Run OXtal inference:
bash run_inference.sh
```

## 📖 Citation
If you make use of this code or its accompanying [paper](https://arxiv.org/abs/2512.06987), please cite this work as follows:
```
@inproceedings{jin2025oxtal,
  title={OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction},
  author={Jin, Emily and Nica, Andrei Cristian and Galkin, Mikhail and Rector-Brooks, Jarrid and Lee, Kin Long Kelvin and Miret, Santiago and Arnold, Frances H and Bronstein, Michael and Bose, Avishek Joey and Tong, Alexander and Liu, Cheng-Hao},
  booktitle={ICLR},
  year={2026}
}
```

## 📄 License

The **source code** for OXtal is released under an MIT License. However, since OXtal was trained on data 
from [CCDC's Cambridge Structural Database](https://www.ccdc.cam.ac.uk/), the **model weights** are released 
under a [Creative Commons Attribution-NonCommercial 4.0 International][cc-by-nc] (CC BY-NC 4.0) License. For commercial 
use of the model weights, please ensure that you have a proper [CCDC License](https://www.ccdc.cam.ac.uk/support-and-resources/licensing-information/).