---
title: 'Reasoning token'
description: 'A provider-reported token used by a reasoning model for intermediate inference work before or alongside its visible answer.'
canonical_url: 'https://darkfactory.dev/glossary/reasoning-token'
markdown_url: 'https://darkfactory.dev/glossary/reasoning-token.md'
collection: glossary
date_published: '2026-08-05T00:00:00-04:00'
date_modified: '2026-08-26T00:00:00-04:00'
---

# Reasoning token


## Definition

A reasoning token is a provider-reported token used for intermediate generation by a reasoning model before or alongside its visible answer. It is an API accounting category, not a standard unit shared by every model provider.

OpenAI reports reasoning tokens within output-token details. Its documentation states that these tokens are not visible through the API, still occupy context-window space, are billed as output, and count toward `max_output_tokens`. Other providers may expose thinking text, summaries, budget controls, or no separate count at all. Read the contract for the exact model and endpoint.

Reasoning tokens are also not a faithful transcript of a model's causal process. A count tells an operator how much provider-defined intermediate generation occurred. It does not prove that the model checked the right facts, followed a sound argument, or used the tokens efficiently.

## Operational significance

Hidden reasoning can make visible output length a poor estimate of cost or capacity. A low maximum-output setting can be exhausted before the answer begins, and a short answer can carry a large output bill. Track detailed usage, incomplete-response reasons, and total multi-call spend when setting budgets.

## Distinguish it from nearby terms

- Output tokens are the broader generated-token category in APIs that include reasoning inside output usage.
- Chain-of-thought is a form of intermediate reasoning content. A reasoning-token count does not necessarily expose that content.
- Test-time compute includes more than token generation and is the broader resource concept.
- A reasoning-effort setting is an input control. Reasoning tokens report what the model used under provider-specific accounting.

## Check your understanding

A response contains 300 visible tokens and 4,000 reported reasoning tokens. Explain which number matters for the user interface, which matters for billing, and why neither proves correctness.

## Also called

thinking token

## Related terms

- [Token](https://darkfactory.dev/glossary/token)
- [Input token](https://darkfactory.dev/glossary/input-token)
- [Output token](https://darkfactory.dev/glossary/output-token)
- [Reasoning model](https://darkfactory.dev/glossary/reasoning-model)
- [Test-time compute](https://darkfactory.dev/glossary/test-time-compute)
- [Token burn](https://darkfactory.dev/glossary/token-burn)

## Related factory areas

- [Model selection, routing & budgets](https://darkfactory.dev/factory/model-routing-budgets)
- [Economics, capacity & factory FinOps](https://darkfactory.dev/factory/economics-finops)

## Evidence and further reading

- [OpenAI API token usage fields](https://platform.openai.com/docs/api-reference/batch/object?api-mode=responses)
- [OpenAI API: Reasoning models](https://developers.openai.com/api/docs/guides/reasoning)
- [Prompt-Induced Waste in Large Reasoning Models](https://arxiv.org/abs/2608.01347)
- [Tokens That Teach, Produce, and Spin](https://nufargaspar.com/writing/tokens-teach-produce-spin)