What Are AI Tokens?

Tokens are the fundamental units that AI language models use to process text. When you send a prompt to ChatGPT, Claude, or any other LLM, your text is first broken into tokens before the model processes it. A token is roughly three-quarters of a word in English — the word "understanding" is two tokens ("under" + "standing"), while short words like "the" or "is" are single tokens. Punctuation, spaces, and special characters also consume tokens. This matters because every AI API charges per token (both input and output), and every model has a maximum token limit called the context window. Understanding tokens helps you write more efficient prompts, estimate costs accurately, and avoid hitting limits that truncate your context.

Token costs vary significantly across models and providers. As of 2026, GPT-4o charges around $2.50 per million input tokens, while Claude Opus costs roughly $15 per million. Output tokens typically cost two to four times more than input tokens because generation is more computationally expensive. For a typical business prompt of 500 words (roughly 670 tokens) with a 300-word response (400 tokens), you might spend fractions of a cent per request — but at scale, these costs compound quickly. Batch processing 10,000 documents could cost anywhere from $5 to $150 depending on the model. This is why token awareness matters for anyone building AI-powered products or running high-volume workflows.

Practical token optimization starts with your prompts. Remove unnecessary preamble, avoid repeating instructions, use concise formatting, and leverage system prompts (which are cached and cheaper on some providers). When working with long documents, summarize or chunk them rather than pasting entire files. Use a token calculator to estimate costs before sending expensive requests. Most importantly, track your usage — understanding your actual token consumption patterns helps you choose the right model for each task, balancing quality against cost.