o1-mini

o1-mini is a large language model developed by OpenAI as part of the o1 series, which is trained using reinforcement learning to perform complex reasoning. Unlike standard language models that respond immediately, o1-mini generates an internal chain of thought before producing its final answer, allowing it to work through multi-step problems more methodically. It supports a 128,000-token context window and a maximum response size of 65,536 tokens.

o1-mini is designed as a faster and more cost-efficient variant within the o1 series, optimized specifically for tasks in coding, mathematics, and science where broad general knowledge is less critical. The o1 model family has demonstrated strong performance on structured reasoning benchmarks, including ranking in the 89th percentile on competitive programming questions on Codeforces, placing among the top 500 US students on an AIME qualifier, and exceeding human PhD-level accuracy on the GPQA benchmark covering physics, biology, and chemistry. Note that o1-mini has a deprecated status on MindStudio, meaning it has been superseded and may no longer be available for new deployments.