711
Dictionary

Token

The atomic unit an LLM reads and generates — roughly ¾ of a word in English.

1 min readupdated 2026-06-22

/ quick answer

A token is a chunk of text (character, subword or word) that an LLM processes. Pricing, context windows and rate limits are all measured in tokens, not characters. The atomic unit an LLM reads and generates — roughly ¾ of a word in English.

The atomic unit an LLM reads and generates — roughly ¾ of a word in English. A token is a chunk of text (character, subword or word) that an LLM processes. Pricing, context windows and rate limits are all measured in tokens, not characters. In practice: 'ChatGPT is great' ≈ 4 tokens. A 4,000-word article is ~5,300 tokens. GPT-4o's 128k context window fits roughly a 300-page book.
Definition
A token is a chunk of text (character, subword or word) that an LLM processes. Pricing, context windows and rate limits are all measured in tokens, not characters.
Example
'ChatGPT is great' ≈ 4 tokens. A 4,000-word article is ~5,300 tokens. GPT-4o's 128k context window fits roughly a 300-page book.

/ frequently asked

What is Token?

A token is a chunk of text (character, subword or word) that an LLM processes. Pricing, context windows and rate limits are all measured in tokens, not characters.

What is an example of Token?

'ChatGPT is great' ≈ 4 tokens. A 4,000-word article is ~5,300 tokens. GPT-4o's 128k context window fits roughly a 300-page book.

Why does Token matter?

The atomic unit an LLM reads and generates — roughly ¾ of a word in English.

What should I learn after Token?

Open the related workflows and prompts further down this page: they show how this idea is applied in a real task, step by step.

/ continue exploring

Related concepts

The vocabulary this page depends on.

  • →Contextual Compression

    Contextual compression is a technique used to reduce the size of the input context for a Large Language Model (LLM) while retaining its most relevant information, typically by summarizing or filtering.

  • →Token Budgeting

    Token budgeting is the strategic allocation and management of token usage within large language model (LLM) operations to control costs and optimize performance.

  • →Token Budget

    A token budget is a predefined limit on the number of tokens an AI application or specific request can consume within a given period or for a single interaction. It is a critical mechanism for controlling costs and managing resource allocation for Large Language Model (LLM) usage.

  • →LLM (Large Language Model)

    A model trained on huge text corpora that predicts the next token to produce human-like language.

all dictionary →

Related workflows

Turn this into a repeatable process.

all workflows →

Related tool stacks

The tools that run it in production.

all tool stacks →

Comparisons & alternatives

Pick between the options.

all comparisons →

Long-form guides on this topic