English

OlmoEarth v1.1: A more efficient family of OlmoEarth models

Computer Vision and Pattern Recognition 2026-05-21 v1 Machine Learning

Abstract

We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training (1.7×1.7 \times reduction in GPU hours required to train our Base models) and inference (2.9×2.9\times reductions in MACs on Sentinel-2 tasks), while maintaining the models' overall performance. All training code is available at github.com/allenai/olmoearth_pretrain.

Keywords

Cite

@article{arxiv.2605.20804,
  title  = {OlmoEarth v1.1: A more efficient family of OlmoEarth models},
  author = {Gabriel Tseng and Yawen Zhang and Favyen Bastani and Henry Herzog and Joseph Redmon and Hadrien Sablon and Piper Wolters and Patrick Alan Johnson and Christopher Wilhelm and Patrick Beukema},
  journal= {arXiv preprint arXiv:2605.20804},
  year   = {2026}
}