AI2 releases OlmoEarth: open-source geospatial foundation models outperforming larger commercial alternatives
The Allen Institute for AI (AI2) released OlmoEarth, a family of open-source multimodal foundation models for Earth observation and geospatial intelligence. The model family comes in four sizes: OlmoEarth-Nano (~1.4M parameters) and Tiny (~6.2M) for fast, cheap inference; Base (~90M) for balanced accuracy/speed; and Large (~300M) for peak performance. Trained on multimodal satellite data (optical, radar, environmental maps), OlmoEarth excels at scene classification, semantic segmentation, object detection, change detection, and regression on single-image and time-series tasks.
OlmoEarth outperforms larger models including Meta's DINOv3, IBM/NASA's Prithvi, IBM's Terramind, CROMA, Panopticon, and AI2's own Satlas and Galileo. It competes with Google DeepMind's AlphaEarth Foundations: on kNN tasks it performs on par or better; fine-tuned, it substantially outperforms. Real-world impact is immediate: Global Mangrove Watch reduced their mapping pipeline from years of data collection/annotation to hours using OlmoEarth, using just 0.1% of their 5.8M labeled samples. The International Food Policy Research Institute is now generating countywide crop maps for Kenya with local field data, enabling faster interventions on food security.
For climate/environment AI architects: OlmoEarth Platform is an integrated end-to-end system (Studio for labeling/fine-tuning, Viewer for exploration, Run for large-scale inference, APIs for workflow integration). The open weights + code + technical paper enable transparency and community audit. Key advantage: smaller models achieve Pareto-optimal performance vs. compute, reducing inference costs and enabling continual re-analysis. Addressable use cases span crop monitoring, mangrove conservation, wildfire risk prediction, and deforestation detection—all requiring frequent refreshes at scale.
Sources
- Primary source
- allenai.org
“OlmoEarth is industry-leading across scene and patch classification, semantic segmentation, object and change detection, and regression in both single-image and time-series domains. OlmoEarth outperforms many recent foundation models from industrial research labs.”
- geoweeknews.com
“Global Mangrove Watch took years to collect, clean, and annotate the data needed to update their global maps. Once OlmoEarth was applied to this work, that process collapsed from years to hours.”
- allenai.org
“OlmoEarth Platform, an open, integrated, end-to-end solution that handles everything from data collection and labeling to training, inference, and deployment.”