# Token

> The unit a language model reads and writes — a word fragment, word or punctuation mark — and the unit its cost and context limits are counted in.

Models do not see text, they see tokens: common words become one token, rare words split into several, and a hundred tokens make roughly seventy-five English words. Every model call is metered in tokens in and tokens out, which is why a chatbot that drags a long document into every message gets expensive fast.

The practical consequence is budgeting: prompt length, conversation history and the answer itself all share the same context window, and pricing is per million tokens, not per request. Techniques like RAG exist largely to spend tokens only on the fragments that matter.

## Related terms

- https://dfieldsolutions.com/en/glossary/context-window.md
- https://dfieldsolutions.com/en/glossary/rag.md
- https://dfieldsolutions.com/en/glossary/llm.md

---

Source: https://dfieldsolutions.com/en/glossary/token
DField Solutions — Dunakeszi, Hungary — dezso@dfieldsolutions.com
Booking: see https://dfieldsolutions.com/en/contact