Olmo 3.1 32B Instruct

OLMo 3.1 32B Instruct is a 32-billion-parameter open-weights language model developed by the Allen Institute for AI (Ai2). It belongs to the OLMo 3 series and is specifically optimized for multi-turn conversation, instruction-following, and tool-use capabilities. The model is released under the Apache 2.0 license as part of Ai2's commitment to transparency, providing the community with weights, code, and training data details.

The model's architecture is a standard decoder-only Transformer. It was pre-trained on the Dolma 3 dataset, a diverse collection of trillions of tokens, and further refined through a post-training pipeline using the Dolci datasets. This process includes supervised fine-tuning (SFT) and reinforcement learning (RL) to enhance its responsiveness and safety. Compared to the original OLMo 3 release, the 3.1 version incorporates longer and more stable training runs to improve performance on reasoning and coding benchmarks.

While the "Think" variant of the OLMo 3.1 family is specialized for long-chain-of-thought reasoning, the Instruct variant focuses on conversational fluency and practical task execution. It is designed to act as a strong foundation for chat-based agents and general-purpose natural language processing tasks, maintaining a balance between knowledge retrieval and instruction adherence.