AI Code Review Cost per Task Calculator

How to use this calculator

1. Enter workload measurements and the rates that match your deployment.
2. Use peak or percentile values when planning service capacity.
3. Select Calculate to update the result and supporting metrics.
4. Review the interpretation and test alternative assumptions.

Formula

Token cost = Σ(tokens by class × price per 1M ÷ 1,000,000)
Compute cost = compute minutes × hourly GPU price ÷ 60
Human cost = verification minutes × hourly labor cost ÷ 60
Cost per task = token + compute + tooling + human cost

What the result means

The main result is estimated variable cost for one completed review. Monthly spend scales that figure by review volume, while the cost breakdown reveals whether model usage, compute, tooling, or human verification is the main driver.

This estimate excludes fixed engineering, storage, networking, taxes, failed requests, and volume commitments unless they are incorporated into the entered rates.

Example calculation

Using 8,000 uncached input tokens at $3 per million, 2,000 cached at $0.30, and 1,500 output at $15 gives $0.0471 in model cost. Adding $0.02 tooling and three minutes of labor at $60/hour gives $3.0671 per review, displayed as $3.07.

Tips for better results

• Copy current prices from your provider invoice or contract.
• Separate cached and uncached input tokens.
• Include failed or retried calls in observed average token volume.
• Use fully loaded labor cost when appropriate.
• Compare automation savings with quality and risk, not cost alone.