Your Repo's Token Burn Rate Settles the Hosting Argument

Description and use

A Python script estimates monthly token burn from git diffs, and a decision table guides choosing between free managed tiers and self‑hosting.

Problem

Teams struggle to decide between free managed tiers and self‑hosting for AI coding models because they lack a concrete metric of token usage.

Outcome

Teams can quickly estimate a lower‑bound monthly token burn from git diffs, calibrate it against real usage, and apply a simple decision table to choose between free managed tiers and self‑hosting, reducing wasted effort and aligning hosting with actual workload.

Workflow

• 1. Clone or navigate to the target repo.
• 2. Run the provided Python script: python3 burn_rate.py /path/to/repo 3 to analyze the last 3 months of diffs.
• 3. The script outputs the total diff tokens and a lower‑bound monthly burn estimate.
• 4. Multiply the estimate by a factor (3–10) to approximate real API usage based on your own logs.
• 5. Compare the resulting monthly burn to the free‑tier allowance (e.g., 10 M tokens).
• 6. Use the decision table to evaluate fit criteria: monthly burn, latency, data boundary, ops capacity.
• 7. Choose free managed tier if burn is <≈1/3 of allowance and other criteria are met; otherwise plan for self‑hosting or paid tier.
• 8. Re‑run the measurement quarterly to keep the decision data‑driven.

Evidence

The number was 1.8 million tokens per month.

Source

Run it with python3 burn_rate.py /path/to/repo 3.

Source

The free managed tier includes a token allowance — the operator's documentation cites 10 million tokens — plus a hosted server.

Source