Reasoning language models (RLMs) or large reasoning models (LRMs) are large language models that are trained further to solve tasks that take several steps of reasoning. They tend to do better on logic, math, and programming tasks than standard LLMs, can revisit and revise earlier steps, and make use of extra computation while answering as another way to scale performance, alongside the number of training examples, parameters, and training compute.