What does GitHub Copilot cost a company?

The Business and Enterprise seat price, published on GitHub's plans page, did not change on June 1, 2026, but the bill now depends on usage: each licence brings a monthly allowance of credits, and chat, agents and code review are paid per token, at the rate of the chosen model.

What consumes credits in GitHub Copilot Business?

Chat, the CLI, the cloud agent, Spaces, Spark and third-party coding agents consume credits, at the per-token rate of the model used. Code completions and next edit suggestions do not consume any and stay included without limit. Code review also consumes GitHub Actions minutes.

What happens when the GitHub Copilot credit allowance runs out?

By default, usage continues and is billed per credit. If the administrator turns off paid usage, consumption is blocked until the next month. GitHub no longer falls back to a cheaper model, and code completions keep working.

What happened to GitHub Copilot premium requests?

They belong to the old per-request billing system. Since June 1, 2026, GitHub counts credits consumed per token, and per-model multipliers only apply to some individual annual subscriptions.

How do you limit the GitHub Copilot bill without holding developers back?

By first looking at who consumes, on which model and for what, in the usage report and then in the logs. Each team then gets its own budget: you cut what runs for nothing, pick the model for the task, and keep open the usage that pays off.

Seat or pay-per-token: which costs less?

It depends on the usage profile. For a heavy user, the seat is often cheaper than the same volume paid per token; for an occasional user, the reverse holds. That profile can be read in the usage logs.

Can consumption be read by team without tracking each developer?

Yes. The analysis covers usage, not people, and its results are grouped by team. Employees know before the measurement what is looked at and what is not. The reading starts from existing logs, with nothing installed on workstations.

GitHub Copilot pricing: what usage changes on the bill

When GitHub Copilot moved to usage-based billing, an IT services firm with several thousand developers saw its bill multiplied by ten. "The x10 on GitHub costs, that's everybody," its head of generative AI told us. Since June 1, 2026, the seat keeps its price, but every chat, agent or code review request is paid at the rate of the chosen model. In the estates we analyse, 5 % of developers consume half of the credits. Two default settings, which take five minutes to check, let the bill run.

TL;DR: Each GitHub Copilot Business or Enterprise licence keeps its price and brings a monthly allowance of credits, pooled across the whole company. Code completions stay included; chat, agents and code review are paid per token, at the model's rate. Beyond the allowance, usage continues and is billed by default. Claude Code and Cursor follow the same logic.

What should you check today in GitHub Copilot billing?

Everything sits in GitHub's billing settings.

1. Open the AI usage report. GitHub breaks down the credits consumed by model, by user, by organisation and by cost centre. The per-user export, covering 31 days at most, gives the model and the repository of every request. 2. Check the two default settings. Usage beyond the allowance is switched on by default for organisations and enterprises, and the option that stops consumption when a budget is reached is switched off by default. As long as nobody touches them, an exceeded budget sends an alert and billing continues. 3. Set budgets by team or by cost centre. A user budget stops that person outright, with no fallback to a cheaper model. The enterprise budget, which GitHub distinguishes from a total monthly budget, only caps what is paid beyond the pooled allowance. 4. Decide which models each organisation may use. Their availability is set by policy. In GitHub's price list, a token of the most expensive model costs a hundred times one of the cheapest.

No field in the report says what task a request served or what it produced.

Should you put quotas everywhere?

The head of generative AI at that IT services firm did: "I put quotas everywhere, yeah. I'm creating frustration. Never mind." He knows who those quotas hit: "the users who cost a lot are the users who adopted it well." He spends his days closing the taps, and he gave us this advice: "Be the ones who reopen them."

At a consulting firm equipped with Claude Code, a uniform cap blocked one of the most productive workstations, where a good share of the work ran automatically. Messages kept landing on the head of AI's Slack: "Please, remove the cap, please," "because otherwise it drives me mad." We recommended changing that workstation's plan. We see caps hit the most advanced users first, rarely the ones who waste.

The other method starts by reading, team by team, what the expensive requests produce, then cuts what runs for nothing and keeps the rest open. A large public transport group already works this way: a default credit for all its developers, and Claude Code opened case by case, with the manager's approval. A quota that is too tight has a side effect too: some developers go back to their personal subscription, which is shadow AI.