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AI agent cost calculator: cost per successful task

Free tool · no signup · by the Grow or Die product team

Cheap tokens do not guarantee cheap outcomes. Divide the cost of all observed attempts by tasks that actually succeeded, using one reporting window and a success definition you can audit.

Calculate with your assumptions

Sample inputs are illustrative. Calculations run locally. Input values are not sent to analytics or included in a shared link; only tool event names and the tool ID are measured.

Enter your assumptions and calculate. Results are estimates, not verified production evidence.

Cost per successful task, not cost per API call

Total observed cost = all model attempts × average cost per attempt + external tool cost
Cost per success = total observed cost / successfully completed tasks

The average must include successful, failed, retried and cancelled calls. External cost is the total for the same window, not a per-call rate; exclude any item already included in the model cost. At least one model attempt per successful task is assumed. Use task IDs to deduplicate completions.

Example: why the cheapest model can lose

150 attempts at $0.02 each plus $1 of tool cost totals $4. With 80 completed tasks, cost per success is $0.05. If a lower-priced setup costs $3 but completes only 40 tasks, it costs $0.075 per success. The first setup is more expensive per period but cheaper per completed outcome; neither comparison proves equal answer quality.

How much does it cost to run an AI agent per month?

There is no single monthly agent price. For one month, add the model cost of every attempt, including billed failures and retries, plus external tools and compute that you have not already counted. Divide that total by distinct successfully completed tasks to calculate cost per success. Use one consistent workload and success definition.

Illustrative monthly budget: 15,000 model attempts × USD 0.02 per attempt + USD 100 of external tools = USD 400. With 8,000 successful tasks, the cost is USD 0.05 per success. Enter 15000, 0.02, 100 and 8000 above to reproduce it. These are assumptions, not provider prices or a promised production cost.

A development quote, an agent subscription and metered API running cost answer different questions. This calculator does not estimate engineering time or automatically price hosting, human review or maintenance; add those costs only when you have evidence, without double counting. Missing billed usage makes the result unknown.

How should running cost inform agent pricing?

Cost per success is a starting point, not a selling price. If an account pays less than its attributable cost, investigate the workflow and price. Include the billing source's observed refunds and fees separately from incurred model cost, and leave room for support and other expenses. Contribution after AI cost is not net profit.

Next, test revenue and usage assumptions with the AI pricing break-even calculator, or reconcile payments and costs in a customer profitability report. To estimate an API attempt from tokens instead of an observed average, use the token cost calculator.

Handle zero success and missing usage honestly

Zero completed tasks means cost per success is undefined, not $0. If even one billed attempt has missing usage or pricing, uncheck complete evidence: total cost and cost per success stay unknown. Do not divide the cost of only successful calls by all tasks.

Define success before comparing providers: for example, a correctly reconciled invoice accepted by a reviewer. Keep rejected, timed-out and duplicate tasks out of the success count. Compare identical task mixes and windows, not one easy demo against a production workload.

Use it to improve an agent

  1. Join every attempt to an opaque task ID and record the observed result.
  2. Reconcile usage and prices, including failed requests and external tools.
  3. Change one factor, such as cache reuse or retry policy; compare both success rate and cost per success.
  4. Check contribution margin after payment fees and refunds; lower operating cost is not automatically profit.

Continue with the retry waste calculator, prompt cache calculator, and AI contribution margin calculator.

Methodology and evidence boundary

This is a transparent arithmetic tool, not a benchmark or model recommendation. Inputs are user estimates until reconciled with time-versioned provider prices and observed request usage. No production customer data or model call is required.