TokenPad
Counting

LLM Cost by Language Comparator

The same meaning costs two or three times more in some languages.

Your input

71 characters1 lines0 tokensor drop a file

Language CostExact
0Token change
Token change0no change
Input tokens0what you pasted
Output tokens0what you would send
Token cost of this result
Output tokens0
As input$0.00
× 100K requests$0.00

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Result
 

Why the multiplier exists

Tokenizer vocabularies are trained on corpora dominated by English. English words earn dedicated tokens; other languages are rebuilt from sub-word fragments or raw bytes.

The effect is largest for non-Latin scripts, where a single character can cost two or three tokens. It is not a defect — it is what optimising a fixed vocabulary for one distribution does to everything outside it.

The business consequence

Your unit economics differ by market. A product priced uniformly worldwide has a materially different gross margin in each region, and the worst margin is exactly where the multiplier is highest.

This is worth knowing before you launch in a market, not after. It also affects which model you should route each locale to.

Frequently asked questions

Are these multipliers exact?
No — they are typical values for equivalent content. Paste your actual translated text into the token counter for a real figure, since technical and conversational text differ substantially within the same language.
Do newer tokenizers help?
Yes. Larger vocabularies improved non-English efficiency noticeably, which was a deliberate goal. The gap narrowed; it did not close.

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