Understanding Tokens: How AI Models Process Text and Why It Matters for Cost, Context, and Agentic AI

What Are Tokens and Why Do They Matter?

A token is the atomic unit of computation for large language models. When you type a prompt into ChatGPT, Claude Code, OpenCode, or Gemini, the model converts your text into a sequence of numerical vectors called tokens, processes them through its neural network, and generates output tokens one at a time. This tokenization step is invisible to the user but determines everything about cost, latency, and context capacity.

The approximate token count for a given text follows:

Nt≈CRN_t \approx \frac{C}{R}

Where