One Copilot code review costs 13 requests. Here is the rest of the maths.

Copilot now bills on usage rather than seats. The headline change is simple. The multipliers underneath it are where teams get surprised.

The change, and the number that matters

All Copilot plans moved to usage-based billing on 1 June 2026, replacing the previous premium-request model with a monthly allotment of GitHub AI Credits.

Per-seat pricing is predictable and usage-based pricing is not, which is the entire story. But the part that catches teams out is not the model itself, it is that a single interaction does not necessarily cost one request.

Copilot code review carries a multiplier of 13. Every time it reviews a pull request, or reviews code in your IDE, your allotment drops by 13. If you wired Copilot review into CI on every PR, work out your monthly PR count and multiply. For a team merging ten pull requests a day, that is a meaningfully different number than the one on the pricing page.

Where the multipliers stack

Advanced reasoning models can consume 5x or 20x a standard request. This is defensible, since a reasoning model genuinely does more work, but it makes model choice a budget decision rather than a preference.

There are discounts too, and they are worth taking. Using auto model selection in Copilot Chat, Copilot CLI, or the Copilot cloud agent earns a 10% multiplier discount, so a model that would bill at 1x bills at 0.9x instead. Letting the platform pick is cheaper than pinning a model, which is the opposite of the instinct most engineers have.

On GitHub Enterprise Cloud, requests processed with data residency or FedRAMP enforcement carry an additional 10% multiplier. If you are in a regulated environment, that is a compliance cost showing up as a line in your AI budget, and it is worth naming it as such when someone asks why the number moved.

Why unattended agents change the risk

Under per-seat pricing, the worst case was bounded: you paid for the seats you had. Under usage-based pricing with agents that run without a human waiting, the worst case is bounded by whatever loop you wrote.

This is the same shape as any metered cloud resource, and the same discipline applies. The reason it surprises people with AI tooling specifically is that the previous model trained everyone to think of it as a fixed cost, so nobody instrumented it.

What to do

Count your monthly pull requests and multiply by 13 before deciding whether Copilot code review runs on every PR or only on ones above a size threshold.

Turn on auto model selection where you can. The 10% discount applies for doing less work, not more.

Treat reasoning models as a deliberate choice per task rather than a default, given the 5x to 20x range.

Set a spend alert now. The first genuinely surprising invoice under a metered model is almost always the one nobody was watching for.

If you are on Enterprise Cloud with data residency or FedRAMP, budget the extra 10% explicitly so it is not mistaken for drift.