Calculator · OpenAI and GPT

OpenAI cost estimator

A workload shape projected across a month: input-heavy extraction and generation-heavy chat land on very different invoices from the same rate card.

How the estimate is computed

Token cost is arithmetic and identical for every provider: input tokens and output tokens are each priced per million tokens and summed. The per-run cost becomes a monthly projection by multiplying with runs per day and days.

monthly = (input tokens x input rate + output tokens x output rate) / 1,000,000 x runs per day x 30

For the full method, from measuring one representative run to reconciling usage after launch, read how to estimate LLM API costs.

What the estimate leaves out

Re-rate the calculation with your own token counts and the current per-million rates published in the model catalogue. Estimates exclude taxes, platform fees, cache rules, minimum purchases, failures and retries; verify a real bill against the provider's usage records.

FAQ

How is the OpenAI cost estimator estimate computed?

Input tokens multiplied by the input rate plus output tokens multiplied by the output rate, divided by one million, then multiplied by runs per day and days. Every step is plain arithmetic you can reproduce.

What does the OpenAI cost estimator estimate exclude?

Taxes, platform fees, cache-specific billing rules, minimum purchases, failed requests and retries. Verify a real bill against the provider usage records.

Where do the per-million rates come from?

Providers publish rates per million tokens; the Rynler model catalogue lists the current values. Rates change over time, so re-rate the calculation with current values before committing to a workload.