Reasoning model
Definition
A reasoning model is an AI language model trained to work through a problem step by step before it gives a final answer. The extra thinking makes it slower and more expensive per answer, and noticeably better at math, coding and other multi-step tasks.
By Ronan Liedmeier, fractional head of growth and course author · Published 17 October 2026 · Last updated 17 October 2026
Also called: thinking model, large reasoning model
Many chat products offer a reasoning or "thinking" mode next to a faster default model.
How it works
A standard large language model starts writing the answer straight away. A reasoning model first produces a long internal chain of steps and can back up and try another approach when one fails. OpenAI's o1, announced in September 2024, was trained with reinforcement learning to work this way, and users saw a summary of its reasoning rather than the raw steps.
It is the trained-in version of chain-of-thought prompting. The step-by-step work happens by default, so you don't have to ask for it.
Example
An analyst asks for the break-even point on a subscription offer with a discounted first year and an expected cancellation rate. The fast model returns a confident figure that ignores cancellations. In reasoning mode the model lays out each step and includes them, and the analyst can check the working line by line instead of trusting a bare number.
Common mistake
Leaving reasoning mode on for every task wastes time and money: classification and short rewrites come back slower with no gain in quality. Test both on your own task. If the fast model's answers hold up, keep it, and save reasoning for work with several dependent steps.
Learn it in AI Academy
- How AI Actually Works (The 20% You Need)Beginner · 12 minFree
- Advanced Prompting in 2026Expert · 7 min
Related terms
- Chain-of-thought prompting
- Chain-of-thought prompting is asking an AI model to work through a problem step by step before giving its final answer. Writing out the steps improves accuracy on multi-step tasks like math and logic problems, and shows the working so you can check it.
- Large language model (LLM)
- A large language model (LLM) is an AI system trained on huge amounts of text to predict which words should come next. At scale, that one skill lets it answer questions, summarize, translate and write in a way that reads like a person wrote it.
- Latency (AI response time)
- Latency is the time an AI system takes to respond, from the moment a request is sent until the answer, or its first words, arrive. In agent workflows it adds up across every model call and tool call in a run.