---
title: "Reasoning model"
type: "glossary term"
url: "https://aifordevs.org/glossary#reasoning-model"
markdown: "https://aifordevs.org/glossary/reasoning-model.md"
publisher: "AI for Devs"
license: "https://aifordevs.org/reuse"
attribution: "Credit AI for Devs and link to https://aifordevs.org/glossary#reasoning-model"
---

# Reasoning model

A reasoning model is a model trained to generate intermediate reasoning tokens before its final answer. It trades latency and output tokens for better results on math, code, and multi-step problems.

OpenAI bills reasoning tokens as output tokens and counts them against the context window, even though the API does not return them. DeepSeek-R1 reports that reinforcement learning alone can produce this behavior, without human-labeled reasoning examples. OpenAI and Anthropic both expose an effort setting that trades reasoning depth for latency and token use.

## Example

A request that returns 300 visible tokens after 3,000 reasoning tokens is billed for 3,300 output tokens.

## Source

[OpenAI docs: Reasoning models](https://developers.openai.com/api/docs/guides/reasoning)

## Related terms

- [Token](https://aifordevs.org/glossary#token)
- [Inference](https://aifordevs.org/glossary#inference)
- [Context window](https://aifordevs.org/glossary#context-window)

## Cite this term

AI for Devs. "Reasoning model." https://aifordevs.org/glossary#reasoning-model

- Page: https://aifordevs.org/glossary#reasoning-model
- Markdown: https://aifordevs.org/glossary/reasoning-model.md
- Reuse: Quote or summarize with a link to this page. Terms: https://aifordevs.org/reuse
- Publisher: AI for Devs