AI Tokenizer
Type or paste any text below and see exactly how a GPT-style language model would break it into tokens, the fundamental units it processes. This is the first step in understanding how AI works.
Tokens
Start typing to see tokens...
What is tokenization?
Before a language model can process your text, it breaks it into smaller pieces called tokens. A token can be a word, part of a word, a space, or even a single character. The model doesn't see your text the way you do. It sees a sequence of token IDs.
This matters because the way text gets tokenized affects everything: how much context the model can process, how much it costs to use, and even how well the model understands your input.
Why should you care?
- Cost control. API pricing is per-token. Knowing how many tokens your prompt uses helps you optimize spending.
- Context limits. Every model has a token limit. Understanding tokenization helps you stay within bounds without cutting important context.
- Better prompts. Some phrasing tokenizes more efficiently than others. Understanding this makes your prompts more effective.
Go deeper in Chapter 2
The tokenizer tool shows you what happens. Chapter 2 of Get Insanely Good at AI explains why it matters, and how understanding the full pipeline from tokenization through transformer processing changes the way you work with AI.
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