---
title: 'Output token'
description: 'A token generated by a model as part of its response, often metered separately from input tokens.'
canonical_url: 'https://darkfactory.dev/glossary/output-token'
markdown_url: 'https://darkfactory.dev/glossary/output-token.md'
collection: glossary
date_published: '2026-08-03T00:00:00-04:00'
date_modified: '2026-08-26T00:00:00-04:00'
---

# Output token


## Definition

An output token is a token generated by a model during an inference call. Visible answer text, serialized tool arguments, and structured data can all contribute to output usage. Providers usually meter output separately from input, often at a different price.

The term can refer narrowly to tokens visible in the returned content or more broadly to a provider's `output_tokens` or `completion_tokens` field. Those meanings are not always identical. OpenAI, for example, reports non-visible reasoning tokens inside output-token accounting for supported reasoning models. Check the API's detailed usage fields before treating visible text length as total generated usage.

## Operational significance

Output tokens affect response time, cost, and context capacity. Streaming changes when the application receives them, not how many the model generated. A short final answer can still follow extensive hidden reasoning or several earlier calls, so per-response output count is only one part of an agent's total inference budget.

An output limit may end generation before a structure is complete. Downstream code should inspect the provider's stop or completion reason and validate the result instead of assuming that returned text is complete.

## Distinguish it from nearby terms

- Input tokens represent the context supplied for the call. Output tokens are generated after the call begins.
- Reasoning tokens are intermediate generated tokens reported by some providers. They may be a subset of output accounting even when they are not exposed as text.
- A maximum-output setting caps generation. It does not report what was actually used.

## Check your understanding

An API returns a 120-token answer but reports 2,400 output tokens, including 2,280 reasoning tokens. Explain why both numbers can be correct and which one belongs in cost accounting.

## Also called

completion token

## Related terms

- [Token](https://darkfactory.dev/glossary/token)
- [Input token](https://darkfactory.dev/glossary/input-token)
- [Reasoning token](https://darkfactory.dev/glossary/reasoning-token)
- [Maximum output tokens](https://darkfactory.dev/glossary/max-tokens)
- [Token burn](https://darkfactory.dev/glossary/token-burn)

## Related factory areas

- [Model selection, routing & budgets](https://darkfactory.dev/factory/model-routing-budgets)

## Evidence and further reading

- [Google Machine Learning Glossary](https://developers.google.com/machine-learning/glossary/)
- [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)
- [Token Budgets](https://arxiv.org/abs/2606.04056)