Unverified50% confidenceFactExact time
OpenAI's BPE tokenizer averages about 4 characters/token for English, but symbols, indentation, and short identifiers in code pull the characters/token ratio down to 3.5~3.8.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
Unverified为英语优化的BPE分词器会将印度语言文本切分为过多子词单元，导致序列长度膨胀和信息密度下降69% similarUnverifiedThe tiktoken tokenizer used by OpenAI is based on a BPE variant, where common English words are typically preserved as whole units while rare words are split into multiple subword units.69% similarUnverifiedUnder naive byte-level tokenization, Bengali is compressed to an average of approximately 1.4 characters per token, compared to approximately 3.9 for English, causing the linguistic balance of the corpus to be inverted.69% similarUnverifiedFor English prose and OpenAI's current tokenizer, 1 token ≈ 4 characters, 1 token ≈ ¾ of a word, and a page of dense A4 text is about 600–800 tokens.69% similarUnverifiedThe ratio of bytes to tokens varies greatly across different tokenizers and character sets: English text is about 4 bytes/token, Chinese about 1.5–3 bytes/token, and JSON Schema commonly falls between 3.5–4.5.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1059286API
curl https://kongchang.com/api/v1/knowledge/claims/1059286MCP
get_claim(id=1059286)