Tokenization under the hood: BPE, WordPiece, SentencePiece, and Unigram compared
The choice of subword tokenization algorithm significantly impacts LLM performance and cost. Algorithms like BPE, WordPiece, SentencePiece, and Unigram determine vocabulary size, handling of rare words, cross-language efficiency, and inference expenses. Understanding these algorithms is crucial for optimizing LLM products, as tokenization directly affects operational costs, vocabulary coverage, and the model's understanding of language. AI
IMPACT Understanding tokenization algorithms is key to optimizing LLM inference costs and model behavior.