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New C++ tokenizer 'quicktok' offers 11x speedup over tiktoken

A new C++ tokenizer called quicktok has been developed, offering significant speed improvements over existing solutions. It achieves byte-identical tokenization to tiktoken and is notably faster, running 2-3.6x faster than bpe-openai and 4-11x faster than tiktoken itself. The tokenizer supports various models including cl100k, o200k, GPT-OSS, Llama-3, and Qwen2.5/3, utilizing data structure engineering for enhanced performance. AI

IMPACT Accelerates tokenization workflows, potentially speeding up LLM inference and training processes.

RANK_REASON The cluster describes a new open-source software release for a specific AI task (tokenization) with benchmark results. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/_casa_nova_ ·

    quicktok: a faster tokenizer (exact and byte-identical with tiktoken) [P]

    <!-- SC_OFF --><div class="md"><p>Been working on this a while! Should be useful for anyone trying to speed up their tokenization workflows.</p> <p><strong>quicktok</strong> is a fast/exact BPE tokenizer written in C++. Token ids are byte-identical to <code>tiktoken</code> and en…