Educational tool · client-side only

Token estimator

This page produces an ESTIMATE of how many tokens a piece of text might use. Real tokenizers differ by model family — exact counts require the model’s own tokenizer. No API keys are used.

Important: Treat every number below as an ESTIMATE. English often lands near ~0.75 words/token, but code, non-English text, and special symbols can diverge sharply.

Diagram of text split into tokens before model input
Text is split into tokens before a language model processes it — boundaries vary by tokenizer.

Estimate tokens

Heuristic

ESTIMATE

Characters
0
Words
0
Estimated tokens
0
Range (illustrative)
0 – 0

Enter text to see an estimate. Different models will disagree on exact counts.

Why counts differ by model

  • Tokenizers use different vocabularies (BPE, SentencePiece, WordPiece, and variants).
  • Whitespace, punctuation, emoji, and code often become multiple tokens.
  • Multilingual text may use far more tokens than English for the same meaning.
  • Provider dashboards and local libraries are the source of truth for billing or context windows.

Read about tokenization · Concept map · Learning hub