Due to Byte-Pair Encoding (BPE) character splits, Russian text generates 1.7× more tokens than equivalent English text. 1,000 Russian words consume ~2,266 tokens in Claude Opus 4.8 (OpenRouter).
Quick answer
For 1,000 Russian words, Claude Opus 4.8 (OpenRouter) is modeled at 2,266 tokens—1.7× the English baseline. That is approximately $0.0113 as input, before any cache discount.
Method & trust
The language page applies the published language multiplier to a 1,333-token English baseline, then applies the model's input/output rates. Tokenizers differ, so benchmark representative text before production budgeting.
Relative to English baseline (1.0×).
Price to send 1,000 words of Russian text into context.
Discounted price for repeated Russian system context.
| Word Count Scale | Russian Tokens | Russian Input Cost | English Equivalent Cost | Tokenization Penalty |
|---|---|---|---|---|
| 1,000 words (Short Article) | 2,266 | $0.0113 | $0.006665 | +$0.004665 |
| 10,000 words (Whitepaper / Report) | 22,661 | $0.1133 | $0.0667 | +$0.0467 |
| 50,000 words (Book / Corpus) | 113,305 | $0.5665 | $0.3333 | +$0.2333 |
| 100,000 words (Enterprise Repository) | 226,610 | $1.133 | $0.6665 | +$0.4666 |
Each Cyrillic character requires more token memory than standard ASCII Latin letters.
Use large-vocabulary frontier models to reduce Cyrillic token fragmentation.
Most LLM tokenizers are primarily trained on English-heavy web datasets. Non-Latin characters in Russian (Cyrillic) split across multiple Byte-Pair Encoding (BPE) sub-word or multi-byte UTF-8 tokens, requiring approximately 1.7× more tokens to encode the exact same semantic meaning as English.
Use large-vocabulary frontier models to reduce Cyrillic token fragmentation. In addition, enabling prompt caching on static Russian instructions or documentation saves 75–90% on input token rates.
Yes. Claude Opus 4.8 (OpenRouter) has strong multilingual comprehension and generation capabilities in Russian (Русский). The difference is purely computational and financial due to sub-word token splits.