Reverse-Engineering the OpenAI's GPT-5 Tokenizer
SMRTR summary
A technical researcher reverse-engineered OpenAI's o200k_base tokenizer used in GPT-4o, GPT-5, and o1 models by downloading and analyzing its complete 200,000-token vocabulary from the open-source tiktoken library. The analysis revealed that OpenAI has doubled vocabulary size at each generation (50k→100k→200k tokens), with the latest version featuring camelCase-aware regex splitting and massive efficiency gains for non-English languages like Arabic (70% fewer tokens) while English prose saw no improvement, suggesting training data heavily weighted toward code and multilingual content.
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