Copilot's Usage-Based Billing Hit 60 Days. Here's What Teams Are Actually Paying.

Two billing cycles have closed since GitHub flipped the switch on June 1. The first cycle was chaos — invoices, screenshots, the usual Reddit meltdown. The second cycle is where the real picture emerges, because by now teams have either adjusted their behaviour or swallowed the new costs. Neither group is happy.

GitHub's line was that base plan pricing wasn't changing. Pro would still be $10. Pro+ still $39. Business still $19 per user. Enterprise still $39. What changed, they said, was that premium features would draw from a monthly bucket of AI Credits — and if you went over, you'd pay for the extra.

Technically true. Practically, it's like saying your rent didn't go up but the kitchen now has a coin slot on the fridge.

How does the pricing actually work?

Every Copilot plan now comes with a monthly allowance of AI Credits. One credit equals one US cent. The buckets:

• **Copilot Business**: 1,900 credits per user per month ($19). Promotional (June-August): 3,000 credits. September onward: 1,900.
• **Copilot Enterprise**: 3,900 credits per user ($39). Promotional: 7,000 credits.

Credits are pooled across the organisation — light users subsidise heavy ones, which is sensible. Credits don't carry over. When the pool runs dry, either usage continues and you're billed at month end, or it stops. Which one happens depends on whether an admin has configured a spending budget. Many haven't.

Code completions and next-edit suggestions remain free and unlimited. Everything else — chat, agent mode, code review, CLI, cloud agent, third-party agents — burns credits at per-token rates. GPT-5.5 long-context output: $45 per million tokens. Claude Opus 4.8: $25 per million. Claude Fable 5: $50 per million. The pricing page lists 30-plus models. Each one is a different line item on your bill.

What are teams actually paying?

The panicked first invoices were one data point. Two cycles in, things have settled into three rough bands. I pulled numbers from GitHub Community discussions, r/GithubCopilot, LinkedIn posts from engineering managers, and a few direct conversations.

**The five-person startup.** On Business at $19 per seat: $95 a month before June. With the promotional 3,000-credit allowance (15,000 pooled), most are staying within the pool. Occasional chat, light code review — it doesn't dent things. The bill remains $95. Fine, for now.

September is the problem. When the allowance drops to 1,900 credits per user, the pool shrinks from 15,000 to 9,500. A team doing three PR reviews a day plus occasional agent sessions will start hitting overages. Nobody at this size has modelled what that looks like.

**The 50-person mid-size team.** $950 a month on Business before June. 150,000 pooled credits at the promotional rate, dropping to 95,000 in September.

What 95,000 credits buys: roughly 95 million tokens at $1 per million. Across 50 developers working 22 days, that's 86,000 tokens per developer per day. Sounds generous until you realise a single agent session reading 30 files and generating 500 lines burns 80,000 to 120,000 tokens. One session eats the day.

One engineering manager on LinkedIn reported their 43-person team burned through the pool by July 18 — 12 days early — and hit $2,800 in overage. Their CTO now mandates manager approval for agent mode. Several developers have quietly gone back to manual coding for anything beyond tab completion.

Then there's the code review sleeper. Copilot's automated PR review runs a full model pass on every pull request. A 500-line PR costs roughly 50,000 tokens, $0.50 to $1.50 depending on model. Fifteen PRs a day across 50 people: $30 a day, $660 a month, on code review alone. Most teams hadn't accounted for it. The billing dashboard doesn't break it out by feature unless you configure the detailed view.

**The 500-person enterprise.** $39 per seat for Enterprise: $19,500 base licence cost. Post-promotion, 1.95 million pooled credits covers roughly $19,500 in AI usage. So your total, if you stay within the pool, is about $39,000 a month.

Most enterprises aren't staying within the pool.

LinkedIn data pegged the average large-team AI coding budget at roughly $85,000 a month after June, up about 36% year over year. That's $45,500 in overage. Some of that is inevitable — bigger codebases, longer sessions, more PRs. Some of it is poor configuration. The spending cap that stops overage charges is off by default. A lot of enterprise admins didn't know it existed until the invoice arrived.

The promotional credits are also a trap. At 7,000 per user through August, enterprises are building workflows at a usage level that becomes unsustainable when the allowance drops to 3,900 in September. The bill doesn't just go up. It doubles.

What's actually driving the cost?

Agent mode is the headline. A multi-file refactoring session can burn 200,000 tokens without breaking a sweat. Developers who run agent mode as their default — the people GitHub spent 18 months marketing it to — are the ones seeing $300 to $750 monthly bills.

Two less obvious drivers deserve attention.

First, model selection. Copilot defaults to the best available model unless you manually pin a cheaper one. If it reaches for Claude Fable 5 at $50 per million output, you're burning credits five times faster than Claude Sonnet 4 at $15. Most developers don't know which model they're hitting. They just know the answer was good.

Second, the third-party agent tax. You can now delegate to Claude Code and Codex through Copilot, but you're paying GitHub's AI Credit markup on top of the third-party agent's own token consumption. Toll road on a toll road.

What are teams doing about it?

**The budget hawks.** Admins are setting hard limits — $50 or $100 per user per month. When the cap hits, Copilot stops. Developers either ration carefully or run out mid-month. Not ideal, but predictable.

**The model pinners.** Teams are defaulting to cheaper models. GPT-5.6 Luna at $6 per million output instead of GPT-5.5 at $30. Worse results, lower bills. Some teams have decided that's fine for non-critical work.

**The switchers.** Heavy Copilot users are moving to flat-rate alternatives. Cursor Pro at $20 a month. Claude Code at $100 for agentic use. Windsurf. These tools will eventually face the same economic pressure — flat-rate AI is a money furnace at scale — but for now, the arbitrage works in the developer's favour.

**The platform buyers.** No-code teams are on governed platforms where AI cost is baked into the subscription. Stacker doesn't bill by token. The inference cost is absorbed into platform pricing. You're not metered on how many AI actions your users trigger. The economics are the platform's problem.

Usage-based billing for AI tools isn't going anywhere. The unit economics of inference make flat-rate unsustainable at scale. But how you consume AI is a choice. You can sit on top of the token meter, tracking every session against a dwindling credit pool, or you can use platforms that abstract the meter away entirely.

The teams treating AI tooling as infrastructure with fixed costs are the ones not refreshing their billing dashboard at 11pm on the 30th. That's where the real advantage sits, and it compounds every month.