How to Estimate AI API Costs Before You Scale

AI API costs can surprise founders who prototype with light usage and then launch to real traffic. Here’s how to estimate before that happens.

Understand token-based pricing

Most LLM APIs charge per token, roughly a chunk of a word, for both what you send the model and what it generates back. Longer conversations, documents, and responses all directly increase cost per request.

Model choice changes cost by orders of magnitude

The most capable models cost meaningfully more per token than smaller, faster models. Many products don’t need the top-tier model for every request; routing simpler queries to a cheaper model can cut costs substantially.

RAG adds hidden costs

Every retrieval-augmented request includes the retrieved context in the prompt, which adds tokens beyond just the user’s question. A large retrieved chunk on every query adds up fast at scale.

Estimate with real numbers before launch

Calculate expected requests per day, average tokens per request including retrieved context, and multiply by your model’s rate. Do this before committing to a pricing model for your own product, not after your first expensive month.

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