✳flâneur — a map of the web's best reading

Reasoning - OpenAI API

platform.openai.com · 5,634 words · saved by 1 readers

OpenAI o1 series models are new large language models trained with reinforcement learning to perform complex reasoning. o1 models think before they answer, and can produce a long internal chain of thought before responding to the user. o1 models excel in scientific reasoning, ranking in the 89th percentile on competitive programming questions (Codeforces), placing among the top 500 students in the US in a qualifier for the USA Math Olympiad (AIME), and exceeding human PhD-level accuracy on a benchmark of physics, biology, and chemistry problems (GPQA). There are two reasoning models available in the API: o1 models offer significant advancements in reasoning, but they are not intended to replace GPT-4o in all use-cases. For applications that need image inputs, function calling, or consistently fast response times, the GPT-4o and GPT-4o mini models will continue to be the right choice. However, if you're aiming to develop applications that demand deep reasoning and can accommodate longer

Reasoning models like GPT-5.5 use internal reasoning tokens before producing a response. This helps the model plan, use tools effectively, inspect alternatives, recover from ambiguity, and solve harder multi-step tasks. Reasoning models work especially well for complex problem solving, coding, scientific reasoning, and multi-step agentic workflows. They’re also the best models for Codex CLI , our lightweight coding agent. Start with gpt-5.6 for most reasoning workloads. If you need the highest-intelligence API option for more challenging problems that can tolerate more latency, use gpt-5.6-sol

Explore this link on the map →

related reading