520 AI Models

Molmo2-8B is an open vision-language model from AI2 that supports image, video, and multi-image understanding. Built on Qwen3-8B with a SigLIP 2 vision backbone, it excels at short-video tasks like counting and captioning while remaining competitive on long-video understanding, outperforming other open-weight, open-data models in its class.

Olmo 3.1 32B Instruct is a 32B-parameter instruction-tuned model optimized for conversational AI and multi-turn dialogue. It focuses on strong instruction following and responsive chat behavior while maintaining solid reasoning and coding performance. Released by AI2 under Apache 2.0, it is fully open and transparent.

Olmo 3.1 32B Think is a 32B-parameter reasoning model built for complex, multi-step logic and advanced instruction following. It improves on earlier Olmo versions with stronger performance on difficult tasks and more refined reasoning. Released by AI2 under Apache 2.0, it remains fully open, with transparent weights, code, and training process.

Olmo 3.1 32B Think is a 32B-parameter reasoning model built for complex, multi-step logic and advanced instruction following. It improves on earlier Olmo versions with more refined reasoning and stronger performance on challenging evaluations, and — as part of AI2’s open initiative — it's fully transparent and released under Apache 2.0 with open weights, code, and training details.

Olmo 3 7B Instruct is a 7B instruction-tuned version of the Olmo 3 base model, optimized for Q&A, instruction following, and natural conversation. Trained with high-quality data in an open pipeline, it performs well on everyday NLP tasks and is easy to adopt. Released by AI2 under Apache 2.0, it provides a transparent, community-friendly choice for instruction-driven applications.

Olmo 3 7B Think is a lightweight reasoning-focused model in the Olmo family, aimed at multi-step problem solving, logical inference, and instruction-driven tasks while keeping conversations coherent. Built by AI2 and released under Apache 2.0, it's fully open and well suited for both research and practical NLP workflows.