Unverified70% confidenceFactTime unknown
中文字符在不同tokenizer下的Token数量差异可达30%-50%
1
Sources
70%
Confidence
Long-term
Relevance
6/2/2026
First Seen
Sources
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Related Claims
UnverifiedThe number of tokens consumed by the same Chinese text may differ by 30%–50% across different large model service providers.75% similarUnverified不同分词算法（BPE、WordPiece等）导致同一段中文文本在不同模型中消耗的Token数量可能相差20%-40%68% similarUnverifiedThe proportion of Chinese data in the pre-training corpora of domestic large models typically reaches 30%–50%, whereas Chinese corpus in overseas models often accounts for less than 10%.62% similarUnverifiedOpus 4.7的Tokenizer在代码注释、中文混排文本和特殊Unicode符号上采用不同合并策略，导致同样文本切分后Token数量可能变为以往的约1.0至1.7倍61% similarUnverified64K token 约等于5万个汉字60% similar
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