Should Your Team Stay on a Free AI Coding Tier? Run This Three-Lane Break-Even Model First

Description and use

A script enables teams to compare costs of free hosted, self-hosted, and paid metered AI coding lanes by calculating cost per accepted change and identifying break-even points.

Problem

Teams need a systematic way to decide whether to use free hosted AI coding services, self-hosted solutions, or paid metered APIs based on cost per accepted change.

Outcome

The script provides a transparent, data-driven cost comparison across free hosted, self-hosted, and paid metered AI coding lanes, enabling teams to identify the most economical option for their usage patterns.

Workflow

• 1. Gather eight key inputs: attempts/month, accept rate, review minutes, reviewer hourly cost, variable cost per attempt, fixed monthly cost, ops hours, infrastructure cost per hour.
• 2. Measure review minutes by timing 30 recent PR reviews with a stopwatch.
• 3. Estimate accept rate per lane by reviewing historical data or pilot runs.
• 4. Populate the script’s LANES data with your own numbers.
• 5. Run the script with desired attempts, loaded hourly, and ops hourly values.
• 6. Review the output: cost per accepted change and total cost for each lane.
• 7. Use the self_host_breakeven function to find the attempts/month where self-hosting equals paid metered cost.
• 8. Present findings to stakeholders and choose the lane that offers the best cost per accepted change for your volume.

Evidence

The script below is a proposal, not a measured result. I have not attached a run log, and every number in LANES is an assumption you are expected to overwrite with your own invoice and calendar data.

Source

Unit: fully loaded cost per accepted change. An accepted change is an AI-assisted change that passes review and is still in the codebase two weeks later.

Source