OpenAI API Cost Calculator

The question 'how much does the OpenAI API cost' doesn't have a single answer, because cost is a product of three genuinely independent variables — request volume, average tokens per request, and model tier pricing — and getting a realistic monthly figure requires estimating all three honestly rather than anchoring on a single request's price, which is exactly the gap this calculator is built to close.

Request volume is usually the variable teams most underestimate at the planning stage, for a reason that's easy to miss: early testing happens at a tiny fraction of real production scale, so a feature that costs a few cents to test manually can look deceptively cheap right up until it launches to actual users and volume jumps by several orders of magnitude. The honest way to budget is to start from a realistic expected user count and typical usage frequency — how many requests does a genuinely active user generate per day, and how many active users do you actually expect — rather than extrapolating from a handful of manual test runs during development.

Average tokens per request is the second variable worth estimating carefully rather than guessing, and it's worth separately estimating input and output length rather than a single blended figure, since they're priced differently and often behave differently across a real feature's actual usage. A summarization feature, for instance, might have a long average input (the document being summarized) and a comparatively short average output (the summary itself), while a creative writing assistant might have the opposite profile — short input prompts driving long generated outputs. Getting this split roughly right matters because output's higher per-token price means a feature's real cost profile depends heavily on which side of the request actually carries more tokens, not just the total.

Model tier pricing is the variable most directly under your control, and it's worth treating as a genuine design decision rather than a fixed cost to simply accept. The gap between a flagship-tier model and a lighter, cheaper tier is often an order of magnitude or more per token, and for many real production tasks — especially high-volume, latency-sensitive ones like classification, tagging, or short-form extraction — a cheaper tier performs adequately well, meaning the model tier choice is frequently the single largest lever available for controlling total API cost at scale, larger in practice than any amount of prompt-length optimization.

Once these three variables are estimated, projecting from daily to monthly and yearly cost is simple multiplication, but it's worth actually doing that multiplication explicitly rather than eyeballing it, since the compounding effect across a full month or year of sustained volume is easy to underestimate mentally — a request that costs a fraction of a cent individually can add up to a genuinely significant monthly line item once multiplied by realistic daily volume across 30 days, and a feature that looks trivially cheap per-request can still represent a meaningful, worth-planning-for cost once true production scale is actually accounted for. Running that full calculation before committing to an architecture — rather than after the first surprising invoice arrives — is exactly the discipline this calculator, and the broader per-token cost estimation workflow it's part of, is meant to support.