GitHub Copilot premium requests moved from a nice‑to‑have concept to a real line item this month. Beginning December 2, 2025, GitHub started removing the legacy “$0 premium‑request budget” that many enterprise and team accounts relied on to block overages by default. If you haven’t set an explicit policy, premium requests can now be billed according to your plan and budget settings. That’s the headline, and it’s why leadership and platform teams should lock in a plan today. (github.blog)
Here’s the thing: “premium requests” isn’t marketing fluff. It’s a clear billing switch that turns on whenever developers pick certain models or features. Additional premium requests beyond a plan’s allowance are priced at $0.04 per request, and some features consume multiple requests per action. Leave this unmanaged for a week and you’ll feel it at the end of the month. (docs.github.com)
GitHub Copilot premium requests: what changed in December?
Two policy updates drive the urgency. First, GitHub enforced monthly allowances for premium requests across paid plans earlier this year. Second—and new this month—$0 account‑level budgets are being removed for older enterprise/team accounts, shifting control to your paid‑usage policy. In other words, if your policy allows paid usage and you don’t set a budget cap, those overages will go through. (github.blog)
What counts as a premium request? Any use of certain advanced models or specific features—agent mode, Copilot Spaces, Spark, code review, and more—consumes premium requests. The pricing unit is simple: one request is the base. But model multipliers change the math (for example, 10× for a heavy model means one prompt can equal 10 requests). Some features also have fixed rates (Spark is four requests per prompt). (docs.github.com)
Good news: on paid plans, you still get unlimited code completions and unlimited chat with the included models (currently GPT‑4.1 and GPT‑4o). That’s the lever we’ll use to contain costs without killing productivity. (github.blog)
The 60‑minute rollout: lock down spend without slowing shipping
Below is a pragmatic sequence we’ve used with clients to eliminate “surprise” bills while keeping developers unblocked. You can do it in under an hour, then refine next week.
1) Choose your default: block paid usage or cap it
Decide whether you want an absolute block (DISABLED) on premium overages or a controlled cap. If your priority is zero risk, set the premium‑request paid usage policy to Disabled. If you want limited overage, set it to Enabled and add a budget (for example, $100 per month) while you learn your baseline. With the December change, this policy—not the old $0 budget—governs whether overages are possible. (github.blog)
2) Create cost centers before you buy a single extra request
Map premium‑request spending to teams or initiatives. Cost centers make later conversations with Finance boring—exactly what you want. GitHub supports cost centers for attributing usage; use them day one. (docs.github.com)
3) Lock the “included models” as the default
Set org guidance in your IDE onboarding doc: default to GPT‑4.1 or GPT‑4o for day‑to‑day chat and completions. These don’t consume premium requests on paid plans. You’ll reduce consumption dramatically while preserving the developer experience. (github.blog)
4) Turn on auto model selection where it helps
Auto model selection can apply a small discount to multipliers in supported environments. If your teams genuinely need premium models, enable auto selection in VS Code and document when to use it. Treat it as a “safety net,” not a license to spray requests. (docs.github.com)
5) Set a starter budget and iterate
A sensible first cap for a 50‑person team is $100–$250/month while you observe usage. It’s small enough to prevent runaway charges but big enough to let a few power users explore agent mode or Spark responsibly. Adjust after two cycles.
6) Publish a short “When to use premium” rubric
Make it explicit: use included models by default; reach for premium models only when you need long‑form refactoring, multi‑repo reasoning, or cross‑tool agent runs. Train one or two “model champions” per team to own experiments and report back.
7) Monitor weekly via IDE and billing reports
Ask leads to check the Copilot status icon and the monthly usage report every Friday. Look for sharp spikes tied to specific people, models, or features. Nudge first, then adjust policy if needed. (github.blog)
8) Trim the riskiest multipliers
If a model carries a 10× multiplier, require a justification (ticket or PR link) before unlocking it for a team. Reserve ultra‑heavy models for release crunches or security reviews. Multipliers directly translate to cost. (docs.github.com)
9) Prefer Spark only for high‑leverage work
Spark charges a fixed four requests per prompt. If your process tolerates it, batch Spark prompts and archive successful prompts into a team wiki to reduce repetition. (docs.github.com)
10) Backstop with budgets by team
Set separate caps by cost center for high‑variance teams (platform, SRE) versus predictable ones (web feature squads). This avoids a noisy “first‑come, first‑serve” drain on a single shared budget. (docs.github.com)
11) Document model do’s and don’ts
Codify this in your engineering handbook alongside your branching strategy. Keep a “green list” (included models) and a “yellow list” (premium models allowed with justification). Update quarterly based on results and GitHub’s changing model roster. (docs.github.com)
12) Share wins with Finance
Report monthly: allowance consumed, overage prevented, and time saved. This is how you protect budget for 2026 without whiplash policy shifts.
How much can this cost? Two quick scenarios
Let’s make the math tangible. Assume $0.04 per premium request beyond your plan’s monthly allowance. We’ll keep the model multiplier at 1× for clarity, then show what happens when it jumps. (docs.github.com)
Scenario A: 50 developers, each exceeds the allowance by 250 requests in a month. That’s 12,500 requests × $0.04 = $500. Not scary—if it’s predictable and valuable.
Scenario B: 10 power users do deep refactors with a 10× model. Each sends 120 prompts. Effective usage is 12,000 requests (10 × 120 × 10 users). At $0.04, that’s $480—on top of regular usage. It adds up fast, especially when mixed with Spark’s fixed four requests per prompt. (docs.github.com)
People also ask
Do code completions count as premium requests?
No. On paid plans, code completions are unlimited and do not consume premium requests. This is why steering most daily work to the included models is a smart first move. (github.blog)
Which models don’t burn premium requests?
Today, GPT‑4.1 and GPT‑4o are included for paid plans and don’t consume premium requests in chat or agent mode. You’ll still see rate limits during peak demand, but not premium charges. (github.blog)
What’s the allowance per plan?
Allowances exist for Free, Pro, Pro+, Business, and Enterprise plans. GitHub’s public pricing page lists 300 monthly premium requests for Pro and 1,500 for Pro+. Business and Enterprise have per‑user allowances as well and support purchasing additional requests. Always verify current limits in your billing console; they can evolve. (github.com)
How do I stop any paid usage right now?
Set your premium‑request paid usage policy to Disabled for the org or enterprise. With the December removal of old $0 budgets, this policy is the control that actually blocks overage. (github.blog)
A simple governance model that doesn’t annoy developers
You don’t need a committee. You need a few rules that engineers can remember:
- Default to included models (GPT‑4.1 or GPT‑4o). Premium only when a task truly needs it.
- Require a ticket link when requesting high‑multiplier models.
- Keep Spark for structured, high‑leverage prompts; batch when possible. (docs.github.com)
- Set per‑team budget caps and revisit monthly. (docs.github.com)
If you want a deeper dive on dialing in these controls, we wrote a hands‑on explainer with additional guardrails—see our guide on how to stop runaway Copilot bills.
Step‑by‑step: your first 7 days
Let’s get practical. Here’s a lightweight, day‑by‑day plan you can copy and run.
Day 1: Freeze the risk
Set premium‑request paid usage to Disabled, or Enabled with a small cap (e.g., $100). Create two cost centers: “Product Engineering” and “Platform/Ops.” (docs.github.com)
Day 2: Baseline your usage
Pull last month’s report. Identify top consumers by feature and model. Look for accidental Spark use or heavy 10× models. (github.blog)
Day 3: Publish your house rules
Post a short policy in the engineering handbook: included models by default; premium allowed with a ticket for complex work; Spark guidance; who can approve temporary boosts.
Day 4: IDE onboarding and defaults
Send a two‑minute “How we use Copilot here” video. Show where to pick models, when to switch, and how to request a temporary allowance.
Day 5: Trial a premium model for a real task
Pick one team, one project, one objective (e.g., migrate a flaky test suite). Track requests consumed and outcome quality. Share results with everyone—good or bad.
Day 6: Adjust budgets by team
Raise caps for teams that showed clear ROI; lower where usage yielded little value. Keep the org cap unchanged for one more month. (docs.github.com)
Day 7: Close the loop
Publish metrics: premium requests used, dollars spent, examples where premium models paid off, and places where included models were enough. Celebrate the boringness of predictable spend.
Why this matters for 2026 planning
AI line items will only grow next year. GitHub is expanding model choices and features (Spark, agents, multi‑model options), with clear SKU‑level attribution and multipliers. That’s good for accountability, but it means your cost curve moves with developer behavior. Be proactive: set policy, budgets, and defaults now so you aren’t rewriting your AI strategy every quarter. (docs.github.com)
What to do next (developers and leaders)
Developers:
- Use GPT‑4.1 or GPT‑4o by default; switch to premium models only with a clear reason. (docs.github.com)
- Batch Spark prompts and save winning prompts to your team wiki. (docs.github.com)
- Watch the IDE usage indicator. If you’re hitting the cap often, talk to your lead about a temporary increase. (github.blog)
Engineering managers and platform leads:
- Set the org’s paid‑usage policy and a starter budget cap today; create cost centers. (docs.github.com)
- Publish a one‑page policy and record a 2‑minute Loom walking through defaults and exceptions.
- Schedule a 30‑minute monthly review with Finance; bring usage reports and examples of value. (github.blog)
Common tripwires (and how to avoid them)
Tripwire 1: A team flips to a high‑multiplier model “temporarily” and forgets to switch back. Solution: add a calendar reminder in the sprint template and set per‑team caps that reset monthly. (docs.github.com)
Tripwire 2: Spark becomes the default for routine prompts. Solution: move Spark behind a hotkey macro labeled “Use when refactoring or researching,” not for daily Q&A. (docs.github.com)
Tripwire 3: Finance sees a spike with no attribution. Solution: turn on cost centers now and require a ticket ID in requests for unlocking premium models. (docs.github.com)
Need a hand getting this right?
If you want help implementing guardrails without slowing your team, our engineers have shipped AI‑assisted workflows across startups and enterprises. See what we do, explore recent work in our portfolio, and reach out via contact for a quick working session. For a deeper dive on spend controls, don’t miss our guide to stopping runaway Copilot bills.
Zooming out, Copilot can absolutely pay for itself—if you channel it. Put these controls in place now, run your 7‑day plan, and you’ll keep developers productive while Finance breathes easy. That’s the balance that wins.
