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How to estimate cost per completed AI task
Learn how to estimate the full cost of an AI task, including input tokens, output tokens, retries, tool calls, latency, and model selection.
Plain-English definition
Cost per completed AI task is the total model-serving spend required to finish one useful workflow, including failed attempts and intermediate calls, rather than only the price of the first prompt.
Memory trick: The useful unit is not cost per prompt. It is cost per finished job.
Why it matters
This unit turns provider prices into buyer math. Coding agents, research agents, and verification workflows often invoke a model several times before one result is usable.
- This unit converts provider token prices into the number a buyer actually plans against.
- Agentic workflows call a model several times before one result is usable.
- Pricing only the first prompt understates a real agent bill by a wide margin.
Simple example
An illustrative task uses 20,000 input tokens at $5 per million and 4,000 output tokens at $25 per million: $0.10 plus $0.10, or $0.20 per attempt. If only four of five attempts succeed, expected cost per completed task is $0.20 / 0.80 = $0.25 before tool fees or overhead.
- Per attempt = input tokens x input rate + output tokens x output rate.
- Per completed task = per-attempt cost / probability of an acceptable result.
- Add tool, retrieval, and orchestration fees before treating the figure as all-in.
Example figures are illustrative calculations, not current quoted market prices.
Market signal
How to read the market signal
A model may increase demand while lowering cost per successful task: higher completion rates can make many more workflows economically viable at the same posted token rates.
- A model can raise demand while cutting cost per completed task via higher completion rates.
- More viable workflows at the same token rate is itself a demand expansion.
- Watch completion rate, not just token price, when judging a release.
Market read: a higher completion rate can expand demand at unchanged token rates by making many more workflows economically viable. Figures here are illustrative unless explicitly sourced and dated — see our methodology.
Common mistake
Do not price only the first response when the real workflow routinely includes retries, verification, context refreshes, and tool rounds.
Practical takeaway
What you can do with this
Estimate input cost plus output cost plus tool or orchestration cost for all expected attempts, then divide by the probability of an acceptable completion.
- Sum input, output, and tool cost across all expected attempts for one workflow.
- Divide by the probability of an acceptable completion to get the planning unit.
- Stress-test the figure at a lower completion rate before committing budget.
Decision check: does your estimate include failed attempts, tool calls, and a realistic completion rate — or only the first prompt?
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