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Peek2: A Regex-free implementation of pretokenizers for Byte-level BPE

Published: January 9, 2026 | arXiv ID: 2601.05833v1

By: Liu Zai

Potential Business Impact:

Makes AI understand words much faster.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

Pretokenization is a crucial, sequential pass in Byte-level BPE tokenizers. Our proposed new implementation, Peek2, serves as a drop-in replacement for cl100k-like pretokenizers used in GPT-3, LLaMa-3, and Qwen-2.5. Designed with performance and safety in mind, Peek2 is Regex-free and delivers a $ 1.11\times $ improvement in overall throughput across the entire Byte-level BPE encoding process. This algorithm runs entirely on the CPU, has stable linear complexity $ O(n) $, and provides presegmentation results identical to those of the original Regex-based pretokenizer.

Page Count
5 pages

Category
Computer Science:
Computation and Language