NSF Mid-Scale RI-2: Open Multimodal AI Infrastructure to Accelerate Science

Ai2 has been awarded a combined $152 million from the U.S. National Science Foundation (NSF) and NVIDIA as part…

MolmoPoint is a new vision-language model architecture that replaces text-based coordinate outputs with a more natural, token-based pointing mechanism that directly selects regions from visual features.

Olmo Hybrid is a fully open 7B language model that combines transformer attention with linear RNN layers to achieve greater expressivity and significantly improved data and compute efficiency compared to pure transformer models.

SERA is the first in our family of Open Coding Agents, achieving state-of-the-art performance at low cost.

Bolmo is new a byte-level family built by adapting Olmo 3 into a fast, flexible byte-based model with a short extra training run.

Molmo 2, a new suite of state-of-the-art vision-language models with open weights, training data, and training code, can analyze videos and multiple images at once.

Our new flagship Olmo 3 model family empowers the open source community with not only state-of-the-art open…

We introduce Deep Research Tulu (DR Tulu), an open post-training recipe and framework for long-form deep research agents.

BAR is a recipe for post-training language models one capability at a time—train domain experts independently, merge them into a single mixture-of-experts model, and upgrade any expert without impacting the others.