TokenAtlas

Token Pricing Explained

The mental model you need to predict and control AI cost.

What is a token?

A token is a chunk of text — roughly 4 characters or 0.75 words in English. AI models read and write in tokens, and providers bill per million tokens consumed.

Why output costs more

Generating a token requires running the entire model. Reading a token is comparatively cheap. That's why output is typically 3–5× input price.

How to estimate your tokens

English text: word_count / 0.75. Code: word_count × 1.5. Non-English: word_count × 2 (conservative). Or use any provider's tokenizer for an exact count.

Per-million rates make comparison easy

All major providers price per 1M tokens. To compare: (cost / 1M) × your_volume. TokenAtlas does this automatically across every model.

Frequently asked questions

Are images and audio tokenized?
Yes — at fixed conversion ratios (e.g. a 1024×1024 image ≈ 765 tokens on GPT-4o).
Do tools/function calls count?
Yes — tool schemas and tool responses are billed as input and output tokens.
Is there a cheaper alternative to tokens?
Embedding APIs bill per token but at fractional rates (~$0.02 / 1M). Use them for retrieval, not generation.

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