SOURCE-LINKED INTELLIGENCE
Fewer Words, Not Fewer Tokens: Measuring the Sanskrit Tokenization Penalty per Proposition
Sanskrit fuses case, number, person and tense into word endings and chains clauses into compounds, so it is information-dense per word. Whether that density survives subword tokenization is a separate question, to be asked per unit of meaning rather than per word. On identical FLORES-200 devtest content, Sanskrit costs 1.774-2.187 times the English tokens under deployed tokenizers with vocabularies of 200,019 ids or more, but only 1.325-1.353 times the Hindi tokens. Against a deployed English tokenizer, Sanskrit-trained BPE arms then look cheaper per proposition than English on contemporary pr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T15:19:48.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.