AI Vocabulary · 01 The Model

What is Token?

The small chunk of text a model reads and writes. Price, speed and memory limits are all counted in tokens.

Basic

A token is the unit a large language model actually works with. Before your text reaches the model, it is cut into tokens: common words are often a single token, rare words, names and numbers are split into several pieces. The model never sees letters or words, only tokens, and it writes its answer one token at a time.

As a rule of thumb, one token is about three quarters of an English word, so 1,000 tokens are roughly 750 words. Other languages, including German, usually need more tokens for the same meaning, and so does unusual text like code, IDs or long numbers.

Tokens are the unit everything else is measured in. The context window is a limit in tokens. Speed is measured in tokens per second. And when you use a model through an API, you pay per token, usually more for the tokens the model writes than for the ones you send in.

Why it matters for you

Tokens turn "AI" into a budget line you can reason about. A long document pasted into every request, a chatty agent that rereads its whole history at every step, a team that sends the same 30-page brief a hundred times a day: all of that is tokens, and tokens are money and waiting time. If an AI bill surprises you, the question to ask is not "which model?" but "how many tokens are we sending, and why?"

Own it

Understanding tokens is the first step to owning your costs. It lets you compare providers on real numbers instead of marketing, notice when a tool quietly sends far more than it needs, and decide when a smaller or local model is good enough. You can't control what you can't count.

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