Starting December 2, 2025, GitHub is removing the legacy $0 Copilot premium‑request budgets that used to block overages for many enterprise and team accounts created before August 22, 2025. From today onward, your organization’s premium request paid usage policy is the gatekeeper. If it’s enabled (the default), usage beyond the monthly allowance is billable; if it’s disabled, premium requests stop when the allowance is exhausted. If you rely on the old $0 budget to prevent spend, this shift affects you. Here’s what GitHub Copilot premium requests mean in practice and what to change right now.
What exactly changed on December 2, 2025?
Historically, many orgs had an account‑level budget of $0 for Copilot premium requests. Hitting the allowance meant Copilot simply blocked premium usage. As of December 2, those old $0 budgets are being removed on eligible enterprise and team accounts. Practically, that means your overage behavior is now governed by the policy switch in Copilot settings:
Enabled (default): allow charges for premium requests beyond the included monthly allowance. Disabled: block premium requests once the allowance is spent. Owners and billing managers receive an email when GitHub removes the old budget, but waiting for that message is how teams get surprised by charges.
How GitHub Copilot premium requests actually work
Every paid Copilot plan includes a monthly allowance of premium requests per user that resets on the first of each month (UTC). As of today’s change:
• Copilot Pro: 300 per month
• Copilot Pro+: 1,500 per month
• Copilot Business: 300 per user per month
• Copilot Enterprise: 1,000 per user per month
Beyond that allowance, additional premium requests cost $0.04 each, and certain models apply a multiplier. Examples you’ll actually feel in your bill:
• GPT‑4.1 and GPT‑4o (included on paid plans): 0× multiplier—no premium requests consumed.
• Gemini 2.5 Pro, GPT‑5, Claude Sonnet 4/4.5: 1×—one prompt equals one premium request.
• Claude Opus 4.1: 10×—one prompt counts as ten premium requests.
• Spark sessions: fixed 4 premium requests per prompt.
Two more gotchas: unused requests don’t roll over, and auto model selection in VS Code can apply a small discount to multipliers, but it won’t save you from unchecked overages if the policy is left open‑ended.
“Are chat and code completions still unlimited?”
On paid plans, code completions and chat with the included models remain unlimited (subject to rate limits). Premium requests are consumed when you use non‑included models or premium features like the coding agent, code review at scale, some extension prompts, or Spark. That’s why one enthusiastic engineer using an expensive model on a long debugging session can move the needle for your monthly bill.
Three real‑world cost scenarios (and how to control them)
1) Quiet creep (most common): You’re on Copilot Business with the default policy enabled. Five developers explore Gemini 2.5 Pro and Claude Sonnet 4 heavily for two days. Each person runs ~250 premium prompts beyond the 300 allowance for the month—1,250 extra requests. At $0.04 each (1× models), that’s $50 of overage. Not terrible—until the rest of the month continues that pattern.
2) The multiplier bite: A staff engineer tries Claude Opus 4.1 to triage a gnarly cross‑repo refactor. A modest 100 prompts at a 10× multiplier becomes 1,000 premium requests—$40 in a single afternoon. Useful? Yes. Surprising if unmanaged? Also yes.
3) Agent‑heavy teams: Your Enterprise seats (1,000 allowance each) are using the coding agent to push feature branches. Two power users go over by 500 prompts each on 1× models—1,000 extra requests equals $40. The agent helps, but you want guardrails so these spikes are intentional, not accidental.
Dec 2 rapid response: a 60‑minute checklist
Here’s a focused, one‑hour pass you can do today to prevent bill shock without blocking useful work.
1) Confirm your policy (10 minutes). In Copilot settings, find Premium request paid usage. If budget protection was your only safety net before, flip the policy to Disabled until you’ve set real caps and alerts.
2) Set a starter cap (15 minutes). Create an organization‑level budget for premium requests that’s high enough to avoid thrash but low enough to catch mistakes—e.g., $100–$250 for a small team, $500–$1,000 for mid‑size. You can raise it later with data.
3) Turn on alerts (5 minutes). Add spend alerts at 50%, 80%, and 95%. Route emails to engineering leadership and the on‑call platform lead, not just finance.
4) Pull last month’s usage (10 minutes). Download premium‑request usage by user. Tag the top 10% of consumers and talk to them first—they’re your early‑warning system and your best signal on where premium models pay off.
5) Lock down model access (10 minutes). Temporarily remove the highest‑multiplier models (e.g., Opus 4.1) for org‑wide defaults. Keep them available only to advanced users who can justify the hit.
6) Communicate the house rules (10 minutes). Post a short note in #eng: which models are “free” on paid plans, how multipliers work, and who to ping for temporary access to pricier models.
A simple governance framework you can reuse
Use the C.L.A.M.P. framework to keep Copilot productive and predictable:
C — Controls: Policy set to Enabled or Disabled intentionally, not by default drift. Limit high‑multiplier models to specific teams.
L — Limits: Budgets and per‑team caps that match your month‑to‑date velocity. Adjust weekly.
A — Alerts: Thresholds that email humans before you cross a bad surprise.
M — Models: Whitelist included models as the default; premium models require a use case.
P — Playbooks: Short guidance for common tasks: PR review, incident triage, refactor planning, and how to request elevated model access.
People also ask
Do unused premium requests roll over?
No. The allowance resets on the 1st of each month (UTC). If you need short‑term bursts late in a month, consider scheduling heavy review or agent runs just after the reset.
What happens if we disable paid usage?
Premium requests stop once users hit their allowance. Developers can still use included models (e.g., GPT‑4o and GPT‑4.1) for chat and completions, subject to rate limits. For most teams, that’s plenty for day‑to‑day coding, with premium models reserved for specific tasks.
Which features consume premium requests?
Examples include: Copilot coding agent, Copilot code review posting comments, Copilot CLI prompts, Spark sessions (4 requests per prompt), and prompts to premium models like Gemini 2.5 Pro or Claude Sonnet 4. Some extensions also meter per prompt.
How do model multipliers affect cost?
Multipliers change how many premium requests a prompt consumes. A 10× model turns ten prompts into the equivalent of 100 premium requests. If you allow overage at $0.04/request, multipliers scale the bill linearly—so a single afternoon on a 10× model can burn a week’s budget.
Policy defaults, seat strategy, and why this matters
Because the overage policy is enabled by default, many orgs have quietly moved from blocked to billable. That’s fine if you’re intentional about it. The trick is right‑sizing your plan and seats. Copilot Business includes 300 premium requests per user per month; Enterprise includes 1,000. If your Business users regularly cross ~800 premium requests, Enterprise can be cheaper than per‑request overage. For everyone else, keep Business seats and enable paid usage with a budget cap so you get the upside without unlimited spend.
Let’s get practical: model policy that won’t annoy devs
Default everyone to included models for chat and completions. Allow premium models at 1× for common tasks (Gemini 2.5 Pro, GPT‑5, Claude Sonnet 4/4.5). Gate the heavy hitters (e.g., Opus 4.1 at 10×) behind a request form or a Slack workflow that expires after 24 hours. It’s the same pattern we use for burstable cloud resources—short‑lived elevation, clear owner, easy rollback.
Telemetry that matters (and what to ignore)
Focus on three metrics: 1) top users by premium requests, 2) distribution of model multipliers, and 3) premium requests per merged PR. The first two tell you who and how; the last tells you whether you’re buying throughput or just buying noise. If premium usage clusters around PRs that never ship, clamp down. If it clusters around incident response or hard migrations that unblock teams, lean in.
Risk and edge cases you should expect
Data residency and reporting: Enterprises using data residency features may have staggered enforcement, but billing behavior for premium requests still applies. Verify reports at the billing entity level; users with multiple licenses must choose the right "Usage billed to" or you’ll misattribute spend.
IDE confusion: Developers can think chat is “free” because it often is with included models. Once they switch models in the IDE, they may not realize multipliers changed. Make the model selector obvious and post a one‑pager in your team wiki.
Extensions and Spark: Some extensions and Spark meter per prompt differently. If your usage spikes and the model report looks reasonable, check extension usage first.
What to do next (today)
• Decide: Enabled or Disabled for paid usage? Pick one—don’t leave it ambiguous.
• Set a budget cap and alerts.
• Pull last month’s usage and talk to the top 10% of consumers.
• Restrict the highest multipliers and document a short approval path.
• Align seats: Business for most, Enterprise for heavy agent or code‑review users.
• Schedule a 30‑minute brown‑bag to explain models, allowances, and multipliers.
Related playbooks and deep dives
If you want templates and step‑by‑step screenshots, we’ve broken this into focused guides:
• Understanding the Dec 2 shift drills into the policy default and who’s affected.
• Your Dec 2 playbook walks through settings and reports to export today.
• Act before Dec 2 explains how to preempt the default change in larger orgs.
• Spend smart now shares budget tiers and alert thresholds that won’t hamstring teams.
Zooming out: treat AI like cloud
Here’s the thing—this isn’t really about Copilot. It’s FinOps for AI. The same guardrails you use for ephemeral compute and data egress apply: sane defaults, budgets with alerts, per‑team caps, and short‑lived elevation for heavier tools. When teams understand the tradeoffs, they’ll pick the right model for the job—most of the time. Your job is to make the right choice the easy one and the expensive choice a conscious one.
If you’d like help setting up policies, usage dashboards, or a lightweight approvals flow, our team has done this across multiple stacks. Start here: our services overview, what we tackle day‑to‑day, and recent client outcomes in our portfolio. We’ll get you from “we hope this won’t spike” to “we know when and why it will.”
