Latest research
October 14, 2026
HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost
HiRO-ACEv2 captures extreme rain, wind, and pressure events at 3 km resolution for about 1/300th the cost of X-SHiELD, making detailed global climate simulations more accessible to researchers.October 9, 2026
Impactful scheduling for GPU clusters
We explain how Ai2’s new GPU scheduler uses time budgets, fair-share allocation, and time-slicing to prioritize high-impact research, shorten queue waits, and keep GPUs busy.October 7, 2026
Now in Nature: Retrofitting language models to operate over bytes
The technique behind Bolmo, Ai2’s fully open byte-level language models, is now published in Nature, with new checkpoints showing the approach generalizes beyond Olmo to other model families.October 2, 2026
Open-sourcing AstaBrief, the fast report-generation model in Asta
We’re releasing AstaBrief, an 8B open-weights model for generating cited scientific reports, available in Asta’s Fast mode or to download and run on your own infrastructure.October 1, 2026
Introducing Olmo-core 3: Open, scalable training infrastructure for large MoEs
Olmo-core 3 introduces a redesigned, fully open training stack for efficiently scaling mixture-of-experts models into the trillion-parameter range.September 1, 2026
BenchMIRT: What are LLM benchmarks actually measuring?
BenchMIRT is a new method for auditing LLM benchmarks question by question, revealing which capabilities they actually measure and helping researchers build smaller, more focused, and easier-to-interpret evaluations.August 7, 2026
TutorMoments: Do AI tutors know when to help and when to hold back?
TutorMoments is an open, replay-based evaluation framework that tests whether AI tutors can recognize when to support a student and when to hold back and encourage deeper reasoning.July 28, 2026
The OlmoEarth Platform: Geospatial inference at planetary scale
How we built the OlmoEarth Platform to fine-tune geospatial models and run continent-scale satellite inference while managing massive data pipelines, distributed compute, and automatically recovering from failures at scale.July 13, 2026
What building Shippy taught us about building agents
Building Shippy taught us that reliable agents depend less on the model itself than on deterministic tools, explicit guardrails, isolated infrastructure, and evaluations grounded in real-world workflows and live data.1-9Next