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Token (AI/LLM)

A token is the basic unit of text that AI language models process — roughly 3/4 of a word in English — and the basis for LLM pricing and context limits.

What Is Token (AI/LLM)?

LLMs do not read words — they read tokens. A token is a piece of text: common words are single tokens ("hello" = 1 token), while uncommon words are split into multiple tokens ("authentication" = 3 tokens). On average, 1 token ≈ 0.75 English words, or about 4 characters.

Why tokens matter: LLM pricing is per-token (input tokens are cheaper than output tokens), context windows limit how much text you can send (GPT-4o: 128K tokens, Claude 3.5: 200K tokens), and longer prompts = higher latency + cost.

Cost optimization: use shorter prompts, cache common responses, choose cheaper models for simple tasks, batch requests, and monitor token usage per feature.

How Groovy Web Uses This

We optimize token usage in every production AI system — reducing costs by 40-60% through prompt optimization, response caching, and intelligent model routing (use cheaper models for simple tasks).

Related Terms

Prompt Engineering

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