Reasoning model
An AI model trained to work through a problem step by step before it gives a final answer.
A reasoning model is an AI system designed to spend extra effort thinking before it responds. Instead of producing an answer straight away, it generates a long chain of intermediate steps, checks its work, and sometimes tries several approaches before settling on one.
This tends to help most on tasks with clear steps, such as mathematics, programming and logic puzzles, where a quick guess is often wrong. It is like the difference between blurting out an answer and working it out on paper. The cost is that answers take longer and use more computing power.
Such models are usually trained with methods that reward correct final answers, so they learn which kinds of step-by-step thinking lead to success. Their rise has changed how progress is discussed, because it shows capability can grow by letting a model think longer, not only by making it larger.
There are open questions. Researchers debate whether the written steps truly reflect how the model reached its answer, or are partly a performance. That matters for safety, since people hope to use the steps to understand and monitor what the system is doing.