GitHub Copilot Premium Requests: What Dec 2 Changed

GitHub Copilot premium requests just got real for enterprise teams. As of December 2, 2025, GitHub began removing legacy $0 budgets on older enterprise and team accounts, shifting control to your organization’s Copilot policy settings and any explicit budgets you set. If your finance and platform teams relied on that default $0 ceiling to block paid overage, you’re suddenly exposed. This guide breaks down what changed, how GitHub Copilot premium requests are actually consumed, and the concrete steps to keep spend predictable while keeping developers fast.

Why this matters to engineering and finance now

Two things collided in Q4: Copilot’s premium requests moved to clearer, product‑specific tracking, and the safety blanket of $0 budgets on older orgs started disappearing. For most companies, the impact isn’t theoretical. The first real invoice after December 1 can include premium usage from the agent mode in Copilot Chat, higher‑end models with multipliers, or features like Spark that burn through allowances faster than basic chat. If you don’t set policy and budgets correctly, a handful of power users can consume a month’s allowance in a day.

Here’s the thing: you don’t need to slow your teams down. You need a rules‑of‑the‑road playbook, visibility, and a few smart defaults.

What exactly changed on December 2, 2025?

Starting December 2, GitHub removed the legacy $0 Copilot premium request budgets for many enterprise and team accounts created before late August 2025. From that point on, paid premium usage isn’t silently blocked by an inherited $0 ceiling; it’s governed by your Copilot “premium request paid usage” policy and any budgets you explicitly configure. If you set no budget and allow paid usage, overage can occur. If you disallow paid usage, users can still run Copilot—just not with premium features beyond their included monthly allowance.

There’s more context around the broader rollout this fall: premium requests have been billed on GitHub.com since June 18, 2025 (and on GitHub Enterprise Server since August 1, 2025), counters reset on the 1st of each month at 00:00:00 UTC, and from November 1, 2025 premium usage began being attributed to dedicated SKUs for better cost tracking. December 2 didn’t invent billing; it removed a default budget that many teams assumed would stay forever.

How GitHub Copilot premium requests actually work

If you want to govern spend, you need to understand the meter. Here’s the quick primer your engineering managers, DevEx team, and finance partner should know.

Requests vs. premium requests

Every Copilot interaction is a request. Some features use more expensive compute or third‑party models and count as premium requests. Paid plans include a monthly allowance of premium requests; once exhausted, users can still use included models and features (subject to rate limits), but premium features either stop or trigger paid overage—depending on your policy and budget.

Monthly reset and time zones

Premium request counters reset on the first calendar day of each month at 00:00:00 UTC. If your finance team allocates cost by local time, remember resets are UTC‑based. That matters for end‑of‑month cutoffs in the Americas.

Free vs. paid plans

Copilot Free provides a capped number of completions and a small pool of premium requests. Paid plans include unlimited completions and chat with included models and a monthly premium allowance for advanced models and features. When the premium pool runs out, users on paid plans fall back to included models unless your policy explicitly forbids additional paid usage.

Included models and model multipliers

Included models don’t consume premium requests on paid plans. Higher‑end models do, and each carries a multiplier. A 1× model consumes one premium request per chat prompt; a 10× model burns ten. Examples today: a top‑tier Claude model may be 10×; a mid‑tier GPT or Gemini model may be 1×; GPT‑4.1 and GPT‑4o have often been treated as included on paid plans. Model catalogs evolve, so don’t hard‑code a list in policy docs—check the current multipliers before you lock budgets.

Pro tip: In VS Code, enabling Copilot’s auto model selection can apply a small multiplier discount on paid plans. That’s a quiet, low‑friction way to stretch your allowance without nagging developers.

Premium features that sip vs. gulp

Not all features are equal. A standard chat prompt on a 1× model uses 1 premium request. Agent mode in Copilot Chat can consume a premium request per prompt (multiplied by the model rate). Spark, a more capable flow, can count as several premium requests per prompt. If your org turns on Spark and agent mode everywhere, your allowance will evaporate faster than you expect.

The 90‑minute governance sprint (run it today)

Here’s a practical, time‑boxed routine we run with clients so you can move quickly without guesswork. Block 90 minutes with one engineering director, one developer productivity lead, and one finance partner.

0–15 minutes: Confirm your baseline

• Open your enterprise’s Copilot usage dashboards. Verify: current month premium usage; top users; top models; features in use (chat, agent mode, Spark).
• Identify which accounts the Dec 2 change affected. Legacy orgs created before late August 2025 likely had the $0 budget removed. Newer orgs already operate under explicit budgets and policies.
• Note existing budgets and whether “premium request paid usage” is allowed or blocked.

15–35 minutes: Decide your default posture

• If you’re risk‑averse this month, set paid premium usage to disallow at the enterprise level. Users keep Copilot, they just can’t exceed the allowance with premium features.
• If your teams rely on premium features, keep paid usage allowed, but set a conservative enterprise budget and enable alerts at 50%, 80%, and 100%.
• For organizations with mixed needs (e.g., platform team vs. product teams), keep the enterprise default tight and grant org‑level exceptions for critical groups only.

35–55 minutes: Optimize models and features

• Set default models to included options for everyday chat; allow opt‑in to 1× premium models for specific repos or teams.
• Enable auto model selection in VS Code to capture the multiplier discount for paid plans.
• Gate Spark and agent mode behind a GitHub team. Start with 25–50 seats for staff/principal engineers and on‑call incident responders, then expand based on usage data.

55–75 minutes: Guardrails and observability

• Turn on weekly usage export to your data warehouse or FinOps tool so finance doesn’t chase screenshots each month.
• Tag usage by cost center using the “Usage billed to” selector where users belong to multiple orgs or enterprises. This prevents phantom cross‑charges.
• Publish a one‑page “Copilot usage norms” doc: what’s included, when to use premium models, and how to request access to Spark or agent mode.

75–90 minutes: Dry run and commit

• Simulate three users hitting common activities (chat, agent mode, Spark) for 10 prompts each and verify the expected consumption in your dashboard the next day.
• Confirm alerting works with a budget threshold test.
• Create a 30‑day check‑in calendar hold to review usage trends and adjust multipliers/models.

How many premium requests will we burn? Realistic scenarios

Let’s make this concrete. Assume one senior engineer spends an hour in Copilot Chat while investigating a flaky integration test and toggles agent mode for two longer tasks. They average 20 prompts, with 4 of them using agent mode. If they stick to a 1× model for basic chat and agent mode is also running at 1×, that’s roughly 20 premium requests consumed. If the agent mode prompts were on a 3× model, those 4 prompts cost 12 premium requests, bringing the total to 28.

Now scale to a squad of ten engineers during a production incident. It’s common to see 50–80 prompts per engineer over a few hours, with a third in agent mode. On a 1× model, that’s 500–800 premium requests. If a subset escalates to a 10× model for deep reasoning prompts, a single person can burn 100 premium requests in 10 prompts. This is why team‑level access control and short‑lived upgrades during incidents are your friend.

If your company has 200 developers and only 30% actively use premium features weekly, you’ll still see spikes at sprint ends, release cutoffs, and incidents. Track the shape of consumption, not just the total, so you can right‑size access to premium features ahead of busy weeks.

People also ask: common Copilot billing questions

Do unused premium requests roll over month to month?

No. When the clock hits 00:00:00 UTC on the first of the month, your unused premium requests reset to zero. If your usage is bursty, favor reassigning access to premium features mid‑month rather than “saving” requests. There’s nothing to save.

What happens when a user runs out of premium requests?

On paid plans, they can keep using Copilot with included models, subject to rate limits. They’ll lose access to premium‑only features and models unless your policy allows paid usage and you have budget available. On Copilot Free, there’s no path to buy more premium requests; the user would need to upgrade.

We have multiple orgs. Who gets billed?

Users with licenses from multiple orgs or enterprises must choose the Usage billed to entity. If they pick the wrong one, you’ll see cost leakage into the wrong cost center. Make the right selection part of your onboarding checklist and audit it quarterly.

Can we “cap” premium usage per user?

Not in a hard, per‑user counter today. You can gate models and features by team, disallow paid overage at the org or enterprise level, and set budgets with alerts that signal when to intervene. That combination behaves like a cap in practice.

Risks, gotchas, and the levers you control

• Hidden spend via high multipliers: A small group on 10× models can dominate your bill. Restrict those models to a named team and require a justification (e.g., incident number, research spike).
• Agents and Spark by default: Turning them on everywhere is a quick way to hit budget limits early in the month. Start with a pilot group, measure, expand.
• Rate limits ≠ free pass: Hitting rate limits on included models doesn’t make premium free. It just slows everyone down. Tune defaults so developers don’t flip to high‑multiplier models out of frustration.
• Multi‑tenant confusion: If users belong to multiple enterprises, they may send premium usage to the wrong entity. Train them on the “Usage billed to” selector and audit outliers.
• Model catalogs change: Included models and multipliers evolve. Review monthly.

A simple decision framework for model access

Give your leads a lightweight rubric so they don’t need a meeting for every request:

• Included models (0× on paid plans): default for all developers, all day.
• 1× models: approved for staff/principal engineers, incident responders, and migration projects.
• ≥3× models: request‑only; time‑boxed for incident windows, security reviews, or deep refactors with an expected hour‑savings target (e.g., “save 10 engineer‑hours this week”).

Make it explicit: if a team can’t show time saved or quality improved, they shouldn’t be on higher multipliers by default.

Policy, budget, and visibility: the trifecta

Your controls live in three places:

• Policy: Toggle whether paid premium usage is allowed at the enterprise and org levels. Use “deny” by default if you lack visibility; turn to “allow with governance” once budgets and alerts are in place.
• Budget: Set monthly budgets for premium requests on the entities that matter (enterprise, orgs). Enable threshold alerts. Don’t bury the alerts in a shared mailbox—route to a slack channel with both DevEx and finance.
• Visibility: Use the usage dashboards, export weekly to your warehouse, and track by team. Label major spikes with context (incident ID, release name) so the data tells a story later.

What changed beyond budgets: SKU clarity helps FP&A

Starting November 1, 2025, premium requests for Spark and the coding agent are tracked as dedicated SKUs. That’s good news for finance: clearer attribution per AI product, simpler variance analysis, and fewer debates about which team consumed what. Pair that with the enterprise budget controls and you can reconcile “pilot” vs. “production” usage without spreadsheets full of approximation.

A quick note on developer experience

Be careful not to turn governance into friction. If you bury developers in approval flows, they’ll avoid Copilot—or worse, switch to unmanaged tools. Two small changes help: set practical defaults that keep included models fast, and allow a one‑click temporary upgrade to a 1× model for a day when someone hits a wall. Your job is to remove drag while keeping the meter sensible.

What to do next

• Run the 90‑minute sprint above and set your default posture for December.
• Gate premium features by team; start with 25–50 seats for your most leveraged engineers.
• Turn on auto model selection in VS Code to squeeze more from the same budget.
• Export usage weekly and route alerts to engineering leadership and finance.
• Revisit multipliers and included models on the first business day of each month, after the UTC reset.

Need a hand making this stick?

If you want help designing policies, budgets, and audits that balance developer speed with cost control, our team does this work every week. See how we structure engagements in our approach to platform and AI governance and browse outcomes in client case studies. For a deeper dive on the Dec 2 change itself and how it interacts with SKUs, start with our write‑up, GitHub Copilot Premium Requests: The Dec 2 Switch. If you’re ready to act now, book a working session and we’ll help you implement the 90‑minute sprint with your real data.

FAQ: Is this the beginning of AI usage‑based everything?

Probably. But you can stay ahead by standardizing how you evaluate new AI features: insist on published multipliers or per‑unit rates, require enterprise‑grade budgets and alerts, and make upgrades time‑boxed by default. Pair that with regular usage reviews and you’ll keep costs proportional to value—without micromanaging every prompt.

Zooming out, Copilot is becoming a standard part of the toolchain. The teams that win won’t be the ones who lock it down or leave it wide open—they’ll be the ones who make the meter predictable, keep the fast path fast, and reserve the expensive models for the few moments when they truly pay back.

If you need a crisp, one‑pager to circulate internally, copy the 90‑minute sprint above, add your enterprise policy screenshots, and drop in your budget thresholds. Then ship it. Your January invoice will thank you.