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2026-03-11 00:00:00:0本报记者 李龙伊3014463310http://paper.people.com.cn/rmrb/pc/content/202603/11/content_30144633.htmlhttp://paper.people.com.cn/rmrb/pad/content/202603/11/content_30144633.html11921 解放军和武警部队代表团新闻发言人答记者问,推荐阅读wps获取更多信息

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Tokenizer EfficiencyThe Sarvam tokenizer is optimized for efficient tokenization across all 22 scheduled Indian languages, spanning 12 different scripts, directly reducing the cost and latency of serving in Indian languages. It outperforms other open-source tokenizers in encoding Indic text efficiently, as measured by the fertility score, which is the average number of tokens required to represent a word. It is significantly more efficient for low-resource languages such as Odia, Santali, and Manipuri (Meitei) compared to other tokenizers. The chart below shows the average fertility of various tokenizers across English and all 22 scheduled languages.

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