What is Tokenization?
The process of breaking down text or visual content into discrete units (tokens) that AI models can process. Fundamental to how AI understands prompts.
How it works
Tokenization converts your text prompt into a sequence of numerical tokens that the AI model can process. The model does not read words directly. It processes tokens, which may represent whole words, word fragments, or special characters. Understanding tokenization explains several practical aspects of prompt engineering: why some words are interpreted differently than expected (they may be split into unexpected tokens), why there are prompt length limits (models have maximum token counts), and why word order matters (the model processes tokens sequentially). Most users do not need to think about tokenization directly, but it explains many prompt engineering behaviors.
Tools that use tokenization
Related terms
Frequently asked questions
What does tokenization mean in AI video?▾
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