A token is the basic unit of text an AI model processes — roughly a word or part of a word. Models read input and generate output as sequences of tokens, and AI usage is almost always measured and priced per token.
How it works
A tokenizer breaks text into tokens before the model processes it. In English, one token is about 0.75 words on average — so 1,000 tokens is roughly 750 words. Both the text you send (input tokens) and the text the model produces (output tokens) are counted.
Why it matters
Tokens are the unit of cost. AI inference is priced per million tokens — a figure that fell roughly 280-fold between late 2022 and late 2024, reshaping the economics of AI. See AI Infrastructure & Compute Statistics 2026.
Related terms: AI Inference · Context Window · LLM · All glossary entries