OlmoEarth v1.1: A more efficient family of OlmoEarth models
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arXiv
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| Format: | Preprint |
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2026
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| author | Tseng, Gabriel Zhang, Yawen Bastani, Favyen Herzog, Henry Redmon, Joseph Sablon, Hadrien Wolters, Piper Johnson, Patrick Alan Wilhelm, Christopher Beukema, Patrick |
| author_facet | Tseng, Gabriel Zhang, Yawen Bastani, Favyen Herzog, Henry Redmon, Joseph Sablon, Hadrien Wolters, Piper Johnson, Patrick Alan Wilhelm, Christopher Beukema, Patrick |
| contents | We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training ($1.7 \times$ reduction in GPU hours required to train our Base models) and inference ($2.9\times$ reductions in MACs on Sentinel-2 tasks), while maintaining the models' overall performance. All training code is available at github.com/allenai/olmoearth_pretrain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_20804 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | OlmoEarth v1.1: A more efficient family of OlmoEarth models Tseng, Gabriel Zhang, Yawen Bastani, Favyen Herzog, Henry Redmon, Joseph Sablon, Hadrien Wolters, Piper Johnson, Patrick Alan Wilhelm, Christopher Beukema, Patrick Computer Vision and Pattern Recognition Machine Learning We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training ($1.7 \times$ reduction in GPU hours required to train our Base models) and inference ($2.9\times$ reductions in MACs on Sentinel-2 tasks), while maintaining the models' overall performance. All training code is available at github.com/allenai/olmoearth_pretrain. |
| title | OlmoEarth v1.1: A more efficient family of OlmoEarth models |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2605.20804 |