Unverified50% confidenceFactExact time
Under the Qwen3 tokenizer, Malayalam averages 13.47 tokens per word, while English averages 1.27 tokens per word.
1
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50%
Confidence
Long-term
Relevance
10/19/2026
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UnverifiedMeasured with the Qwen3 tokenizer on FLORES devtest sentences, Hindi consumes 4.44 times as many tokens per sentence as English.79% similarUnverifiedIn large language models, one English word typically corresponds to 1–2 tokens, one Chinese character typically corresponds to 1.5–2.5 tokens, and GPT-4's single-conversation context window is approximately 128,000 tokens.67% similarUnverifiedQwen的参数规模从70亿到数千亿不等，训练数据涵盖中英文及多语言语料65% similarUnverifiedThe Qwen series vocabulary is mainly Chinese and English with limited subword coverage for Indian languages, whereas Gemma-3 and Sarvam-M included more Indian language data in training and therefore segment more efficiently.64% 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.64% similar
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