README.md

metadata

license: mit
datasets:
  - Zatom-AI/qm9
  - Zatom-AI/mp_20
  - Zatom-AI/geom
  - Zatom-AI/matbench
  - Zatom-AI/qmof
  - Zatom-AI/omol25
  - Zatom-AI/mptrj
language:
  - en
pipeline_tag: graph-ml
tags:
  - chemistry
  - biology
  - foundation-model
  - generative-model
  - predictive-model
  - representation-learning
  - transformer
  - molecule
  - material
  - property
  - energy
  - forces
  - mlip

Zatom-1

This repository contains the model weights for Zatom-1, as introduced in Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials.

GitHub repository

https://github.com/Zatom-AI/zatom

Open-source resources

Zatom-1 builds upon the source code and data from the following projects:

• all-atom-diffusion-transformer
• flow_matching
• flowmm
• jvp_flash_attention
• lemat-genbench
• lightning-hydra-template
• PlatonicTransformers
• ProteinWorkshop
• posebusters
• tabasco

We thank all their contributors and maintainers!

Acknowledgements

This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using AI4Sci@NERSC award NERSC DDR-ERCAP0036206 awarded to AM. NBE would like to acknowledge support from the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, EXPRESS: 2025 Exploratory Research for Extreme-Scale Science program, and the Scientific Discovery through Advanced Computing (SciDAC) program, under Contract Number DE-AC02-05CH11231 at Berkeley Lab.

Citation

If you use the code or data associated with this package or otherwise find this work useful, please cite:

@article{zatom_1_2026,
    title={Zatom-1: A Multimodal Flow Foundation Model for 3D Molecules and Materials},
    author={Alex Morehead* and Miruna Cretu* and Antonia Panescu* and Rishabh Anand* and Maurice Weiler* and Tynan Perez* and Samuel Blau and Steven Farrell and Wahid Bhimji and Anubhav Jain and Hrushikesh Sahasrabuddhe and Pietro Liò and Tommi Jaakkola and Rafael Gómez-Bombarelli and Rex Ying* and Ben Erichson* and Michael Mahoney*},
    year={2026},
    eprint={2602.22251},
    archivePrefix={arXiv},
    primaryClass={cs.LG},
    url={https://arxiv.org/abs/2602.22251},
    note={* denotes equal contribution}
}