What is Tokenization?
Tokenization is the process of converting text (character string) into a sequence of tokens — units that the AI model processes. A token is typically a word fragment (3-4 characters in European languages).
Why does tokenization matter?
Tokenization directly impacts: cost (APIs charge per token), context limits (context windows are measured in tokens), and quality (models trained primarily on English tokenize other languages less efficiently, requiring more tokens and degrading results).
Cost optimization
In enterprise, tokenization optimization brings real savings: concise prompts instead of verbose ones, caching repetitive queries, choosing models with efficient tokenizers for your language, and routing simple tasks to cheaper models with lower token consumption.