o1

OpenAI o1 is a large language model trained with reinforcement learning to perform complex reasoning tasks. Unlike traditional generative models that provide immediate responses, o1 utilizes a private chain of thought to process information, allowing it to refine its logic, evaluate different strategies, and correct its own mistakes before delivering an answer. This reasoning-heavy approach is specifically designed to handle difficult problems in mathematics, science, and computer programming.\n\n## Capabilities and Performance\nThe model demonstrates significant improvements in STEM-related fields compared to previous iterations. In internal evaluations and standardized testing, o1 has achieved performance levels comparable to PhD students in physics, chemistry, and biology. In mathematics, it significantly outperforms earlier models on the American Invitational Mathematics Examination (AIME). Its architecture is optimized for accuracy in technical reasoning, making it particularly effective for generating and debugging complex code or solving multi-step scientific equations.\n\n## Model Variants\nThe series includes the standard o1 model and o1-mini, a smaller and more efficient version. While the full o1 model possesses broader world knowledge and more robust general reasoning, o1-mini is specifically tuned for speed and cost-effectiveness in coding and math tasks. Both models share the same fundamental reinforcement learning framework that prioritizes deliberate logical processing over token-generation speed.