Due to Byte-Pair Encoding (BPE) character splits, Chinese (Simplified) text generates 1.45× more tokens than equivalent English text. 1,000 Chinese (Simplified) words consume ~1,933 tokens in DeepSeek V4 Flash Vision Exp.
Quick answer
For 1,000 Chinese (Simplified) words, DeepSeek V4 Flash Vision Exp is modeled at 1,933 tokens—1.45× the English baseline. That is approximately $0.000851 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 Chinese (Simplified) text into context.
Discounted price for repeated Chinese (Simplified) system context.
| Word Count Scale | Chinese (Simplified) Tokens | Chinese (Simplified) Input Cost | English Equivalent Cost | Tokenization Penalty |
|---|---|---|---|---|
| 1,000 words (Short Article) | 1,933 | $0.000851 | $0.000587 | +$0.000264 |
| 10,000 words (Whitepaper / Report) | 19,329 | $0.008505 | $0.005865 | +$0.00264 |
| 50,000 words (Book / Corpus) | 96,643 | $0.0425 | $0.0293 | +$0.0132 |
| 100,000 words (Enterprise Repository) | 193,285 | $0.085 | $0.0587 | +$0.0264 |
Rare characters and idioms still decompose into multi-byte UTF-8 token sequences.
Models like DeepSeek V4 and Z.ai's GLM-5.3 family are natively optimized with extensive Chinese vocabularies for maximum cost efficiency.
Most LLM tokenizers are primarily trained on English-heavy web datasets. Non-Latin characters in Chinese (Simplified) (Hanzi) split across multiple Byte-Pair Encoding (BPE) sub-word or multi-byte UTF-8 tokens, requiring approximately 1.45× more tokens to encode the exact same semantic meaning as English.
Models like DeepSeek V4 and Z.ai's GLM-5.3 family are natively optimized with extensive Chinese vocabularies for maximum cost efficiency. In addition, enabling prompt caching on static Chinese (Simplified) instructions or documentation saves 75–90% on input token rates.
Yes. DeepSeek V4 Flash Vision Exp has strong multilingual comprehension and generation capabilities in Chinese (Simplified) (简体中文). The difference is purely computational and financial due to sub-word token splits.