KodeKloud

Every AI Request Has a Price and It's Paid in Tokens.💲

The video explains that tokens are the fundamental unit of cost and capacity in large language models, acting like currency for each interaction. It details how tokenization works: common words become single tokens, while rarer or longer words are broken into sub‑tokens—e.g., "tokenization" splits into "token" and "ization," and "anthropomorphization" into five pieces. Code syntax and non‑English text also generate more tokens per meaning. A notable quote underscores the pattern: "The more often a word appeared in training data, the more likely it gets its own single token." The presenter adds a rule of thumb—one token roughly equals four English characters. Implications are clear for developers: token counts directly affect API pricing and prompt length limits, so optimizing language, especially in multilingual or code‑heavy contexts, can reduce costs and improve model efficiency.