Optimal-Delay Online Tokenization Algorithm Achieves Up to 34.8x Lower Latency
Tokenization is usually treated as a solved preprocessing step, so the result that streaming tokenizers can hit provably optimal delay reframes a real bottleneck for serving latency, especially time-to-first-token. Teams building inference infrastructure can swap in this algorithm without changing tokenizer semantics, since it works with tiktoken and HuggingFace vocabularies. The lower-bound proof also signals that further constant-factor gains are unlikely, which narrows where optimization effort should go.
