# How an LLM Turns Words Into Numbers — and What Those Numbers Cost > Source: > Published: 2026-07-24 08:38:53+00:00 Member-only story # How an LLM Turns Words Into Numbers — and What Those Numbers Cost A language model can’t read. It has no letters and no words — only numbers. So the first thing that happens to your sentence is a translation, and that translation quietly decides your bill. Let’s follow one real sentence all the way through. ### Step 1: Break the sentence into tokens The model works with tokens — fragments usually bigger than a letter and often smaller than a word. Common words stay whole; rare ones split into reusable pieces. Take this sentence: “I love tokenizing unhappiness.” It breaks apart roughly like this: ``` ["I", " love", " token", "izing", " un", "happiness", "."] ``` Seven tokens from four words. Look at the split: `love` stayed whole (it's common), but `tokenizing` became `token` + `izing` , and `unhappiness` became `un` + `happiness` . That `izing` piece is reused across *organizing*, *realizing*, *criticizing* — the model learned it once. The lesson is already visible: short common words are cheap, long rare words are expensive. ### Step 2: Turn tokens into numbers Each token has a fixed entry in the model’s vocabulary — an integer ID: ``` ["I", " love", " token", "izing", " un", "happiness", "."]… ```