Token cost by language

What the data shows

On the newer o200k_base encoding, the same text costs between 1.02× (Chinese (Simplified)) and 1.93× (Greek) of the English token count. On the older cl100k_base encoding the range is 1.20× (Portuguese) to 4.99× (Bengali).

The newer encoding helps most where the older one was weakest: Bengali needs 69% fewer tokens on o200k_base, while Portuguese, which was already efficient, saves 8%. Latin-script languages cluster close to English on both encodings. Scripts such as Bengali, Greek, Thai and Hindi were the most expensive on cl100k_base and improved the most.

Two things pull in opposite directions for East Asian languages. They have the fewest characters per token (Chinese (Traditional) has 1.20 on o200k_base), but they also need far fewer characters to say the same thing, so their total cost lands closer to English than the characters-per-token figure suggests. That is why we compare total tokens against the English version, not characters per token alone.

How we measured it

For each language we took this site's own homepage copy: the tagline, the two "what is an online clipboard" paragraphs and the four how-to steps, joined with blank lines. We counted tokens for that text with the o200k_base and cl100k_base encodings using the open-source gpt-tokenizer library (version 4.0.0), a port of OpenAI's tiktoken. The ratio columns divide each language's count by the English count for the same encoding. The numbers are recomputed every time the site is built, on 2026-10-09.

Limits to keep in mind. The translations were written by this site and have not been reviewed by professional translators, and the wording chosen affects length and therefore token count. The sample is one kind of text, short marketing and instructional copy, and about 902 characters in English. Code, legal text, names and numbers behave differently. Treat the ratios as a guide to the size of the effect, and measure your own text for any decision that costs money.

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Cite this data

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WebClipboard. "Token cost by language: 30 languages, two OpenAI tokenizers." 2026-10-09. https://webclipboard.online/token-cost-by-language/