In plain English
Some AI models are optimized to produce answers quickly, while reasoning models are designed to perform additional internal processing when a problem requires it. This can help them break down difficult tasks, consider alternatives, and work through multiple steps before responding. They are particularly useful for mathematics, programming, planning, and complex analysis. Extra reasoning can improve performance, but doesn't make the model infallible.
Example
A reasoning model analyzes a programming bug, considers several possible causes, and develops a solution based on the evidence in the code.