OXtal-CSP/

OXtal

OXtal (Organic 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 (ICLR 2026).

To run inference, please follow the installation instructions in the official GitHub repository. You can then run generation using the provided runner:

# Run OXtal inference:
bash run_inference.sh

If you make use of this code or its accompanying paper, 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}
}

The source code for OXtal is released under an MIT License. However, since OXtal was trained on data from CCDC's Cambridge Structural Database, 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.