Estimate what an AI feature will actually cost to run. Set the tokens per request and your volume to see cost per call, per day, per month and per year — then compare models across providers to find the cheapest one that does the job.
Reused prompt prefix, billed at ~25% (rough).
Indicative list prices in USD, last reviewed —. Providers change pricing and offer batch/cached discounts — confirm on the provider's page before budgeting.
Monthly cost for the same tokens and volume. Cheapest first; your pick is highlighted.
Output usually dominates
Output tokens are typically 3–5× the input price. A verbose model that writes long answers can cost more than a pricier model told to be terse. Cap output length first.
Right-size the model
A small model at a tenth of the price often handles classification, extraction, and routing fine. Reserve the flagship for the calls that genuinely need it.
Caching and batch cut bills
Reused prompt prefixes (cached input) and asynchronous batch endpoints are heavily discounted by most providers — worth it once volume is real.
Cost per request = (input tokens ÷ 1,000,000 × input price) + (output tokens ÷ 1,000,000 × output price). Multiply by requests per day for daily spend, then by 30.44 for a month. Input and output are priced separately, and providers quote per million tokens.
A token is a chunk of text — roughly 4 characters or 0.75 words in English. Both your prompt (input) and the model's reply (output) count.
Generating tokens costs more compute than reading them, so output is usually priced 3–5× higher. Long completions can dominate your bill — trimming output length is often the fastest saving.
They're indicative list prices, dated in the tool. Providers change pricing and offer batch, cached, and committed-use discounts. Always confirm on the provider's pricing page before budgeting.
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