TestingCatalog News’ Post

Usage-based billing was inevitable. The current premium request model didn’t really map to consumption. As a customer, that simplicity of premium requests was a big part of the appeal. But GitHub’s rollout is rough. Not a great customer experience to say the billing model changes June 1, then say customers will know the cost impact sometime in May, after the infrastructure to measure usage is ready. GitHub usually understands developers and enterprise customers better than this. https://lnkd.in/dg-7Z85h

For now, it impacts individual suscriptions. But those enterprises deploying Github Copilot Business or Enterprise may get some anxiety about their future plans. "Exclusive: Microsoft To Shift GitHub Copilot Users To Token-Based Billing, Tighten Rate Limits"

GitHub Copilot is changing its pricing model and moving to usage-based billing from June 1, 2026. Previously, pricing was based on “premium requests”, basically the number of prompts you sent while using premium models. On the Pro plan, that was 300 per month. From June 1, this changes. Instead, every plan will include a monthly amount of “AI credits” (1 credit = $0.01). Usage will then consume credits based on the number of input, output, and cached tokens used by the model. For Business plans (Copilot Business and Enterprise), credits are pooled. Example: an enterprise with 100 Copilot Business users gets a shared pool of ~190,000 AI credits instead of 100 individual limits. Heavy users can consume more, lighter users balance it out. My personal take: Copilot will likely become noticeably more expensive with this model. And I think this is another sign that the era of flat subscription-based coding agents is ending. If you pay per use anyway, and unused credits do not roll over from month to month, then token efficiency suddenly matters much more. Especially for people using coding agents heavily or integrating them deeply into their workflow. Good news: there are already approaches to reduce token usage without losing quality. Example: https://lnkd.in/dNh2-kb2 Also: review your AGENTS.md and keep it short and precise. Disable MCP servers you don’t need now. Official sources: Press release: https://lnkd.in/deN6nPQe Pricing details: https://lnkd.in/dQ7cd97V For OpenAI models, GitHub’s listed model rates appear aligned with token-based API-style pricing: https://lnkd.in/dMbsM5d3

One interesting thing about GitHub Copilot is its Premium Requests billing is per, well, request rather than per token. Requests are 3.33¢ apiece on Pro, 2.6¢ apiece on Pro+, 6.33¢ on Business, 3.9¢ on Enterprise. Triple those figures for Opus. This means that there's a point that, for a given request, it's cheaper to use Copilot's API than Anthropic's, and that's actually an apples-to-apples comparison because GitHub is way less picky about how you use their subscription plans than Anthropic is (e.g. Copilot will happily SSO into Zed). Other reason I use Zed as an example here is it seems to be rather light on total API request count, so the fact that the "cross point" on Opus is on the order of 15k uncached input tokens + 1k output tokens (using the $10 plan) puts Copilot's billing model in the lead for working with larger codebases where you're pulling in a lot of context that's unique to the situation at hand. (edited from my original post because I misremembered input token cost per million) The numbers look a bit better for Sonnet (or GPT 5.4 or Gemini) of course, but I can push reasonably hard even on the 300-request-per-month plan, and "better" only works if the same workload is either relatively turn-efficient or token-efficient, which...Opus 4.6 is pretty darned turn-efficient. Of course this means there's some level of subsidy built into these prices, even though I'm sure these models are running on Azure rather than wherever Anthropic decides to serve their normal API from, but not to the extent of Claude plans, and the limits are monthly rather than every-five-hours/weekly so there's less of the unhealthy "babe wake up the agents stopped churning" urge going on.

All change for the billing in GitHub Copilot. As many people expected was coming, the period of companies such as GitHub subsidizing our AI token consumption is coming to an end. GitHub have announced that from June they will swap to token/usage based billing as opposed to their current flat rate premium request model. This means AI requests will be vary in cost based on their complexity, not just be a single fixed cost irrespective of their complexity. This means the cost of using GitHub Copilot will increase for most organisations. Every GitHub admin should take a close look at the budget and cost centre settings. For more details see https://lnkd.in/eic9rM4y

#GitHub has announced changes to Copilot pricing, with the company now moving to a usage-based billing format. The company currently uses a premium request unit (PRU) billing system, giving subscribers a set number of credits to spend for more complex queries. Under the new setup, GitHub said usage-based billing will better align pricing with how Copilot is being used. In a blog post detailing the move, GitHub’s chief product officer Mario Rodriguez noted the move comes in direct response to surging compute and inference demands. Read more here: https://lnkd.in/e-XX3BNd

Hitting GitHub Copilot Rate Limits? Here’s How to Keep Your Workflow Moving- As GitHub Copilot becomes more agentic and workloads become longer‑running and parallel, many developers are running into session and weekly rate limits. it’s a natural outcome of higher‑velocity, higher‑compute workflows introduced by agents and sub‑agents. The problem: Rate limits increasingly interrupt flow just when teams are scaling AI‑assisted development — especially with parallel tasks, heavy models, and long‑running sessions. GitHub has been explicit about why these guardrails exist: to protect reliability as usage patterns intensify. 3 practical ways to avoid hitting the limit: 1.Use smaller‑multiplier models for simpler tasks Not every task needs the most powerful model. Higher multipliers burn through limits faster — reserving heavyweight models for complex reasoning helps stretch usage efficiently. 2. Switch to plan mode for structured work Using plan mode in VS Code or Copilot CLI improves task efficiency and success rate. Better planning reduces wasted tokens and reruns. 3. Reduce parallel workflows Highly parallel tools (like /fleet) dramatically increase token consumption. Reserving them for high‑leverage moments — instead of default usage — helps avoid surprise limits. Closing thought: As Copilot evolves from “assistant” to autonomous collaborator, cost, limits, and efficiency become design concerns — not afterthoughts. The teams that win won’t just prompt better; they’ll architect their AI usage intentionally. 📖 Full GitHub announcement: https://lnkd.in/gz6j4DzY #GitHubCopilot #AIDevelopment #EngineeringLeadership #DevEx #AgenticAI #SoftwareStewardship

The End of Unlimited: Decoding GitHub's Move to Token-Based Billing For two years, we’ve enjoyed a flat-rate "Premium Request" system. As of June 1, 2026, GitHub is aligning with the rest of the industry (and its own compute costs) by moving to GitHub AI Credits.  1. What Stays the Same? • Base Subscription Prices: Copilot Pro remains $10/month, Business is $19/user, and Enterprise is $39/user.  • Unlimited Completions: Standard code completions and "Next Edit Suggestions" in the IDE still do not consume AI Credits.  2. What is Changing? Instead of a request limit, each plan now includes a credit allotment: • Copilot Pro ($10): Includes $10 in monthly AI Credits.  • Copilot Pro+ ($39): Includes $39 in monthly AI Credits.  • Promotional Bonus: For the first 3 months (June–Aug 2026), Business/Enterprise users get a massive boost ($30 and $70 in credits respectively) before it reverts to their base subscription price.  3. The New "Token Tax" Costs are now calculated by Token Consumption. This means a high-reasoning model like Claude Opus 4.7 or GPT-5.5 will "drain" your credits significantly faster than a lean model. • Input + Output + Cached tokens all count toward the total.  • Copilot Code Review will now consume both GitHub AI Credits and GitHub Action minutes.  4. Admin Controls Enterprise admins now have "Budget Mission Control." You can set spend caps at the organization or even user level. When a user runs out of credits, you can choose to either block additional usage or allow "Pay-as-you-go" overages. The Bottom Line: GitHub is effectively passing the "Compute Bill" back to the power user. If you use lean models for 80% of your work, your bill won't change. If you run heavy agentic workflows through Enterprise models, your "Unlimited" days are over. Are you ready to audit your team's token usage, or will you just increase the budget and hope for the best? Checkout 👉 https://lnkd.in/dpZ-zkys #githubcopilot

The party is over. 🎉 GitHub Copilot just announced usage-based billing, and the new multipliers say enough: Sonnet goes from 1x to 9x, Opus from 3x to 27x. A long Copilot session that used to count as one premium request now costs what it actually costs. None of this should be a surprise. What we've had for the past two years was a subsidy. Hook first, build dependency, monetise later. GitHub's own words give it away: "align pricing with actual usage and build a sustainable business." Per-request pricing was never going to survive agentic coding. The surprise isn't that it ended, it's that it took this long. The practical consequence is straightforward: at these rates, going direct is cheaper. OpenRouter, the Anthropic API, direct OpenAI access, all of them now undercut what Copilot charges once you do the maths. And for teams with stricter data requirements, hosting models directly on Azure AI Foundry or Google Vertex gives you the same frontier models at infrastructure cost, with no platform markup on top. The IDE integration is nice, but it's not 9x nice. What it makes me wonder is what happens inside enterprises. A lot of companies are signing Copilot contracts driven by AI FOMO, leadership mandating AI adoption without a clear picture of what it costs at scale or where it actually creates value. Open-source models like DeepSeek will eventually force prices back down. But by then, most of the contracts will be signed, the vendors locked in, and the damage done.

GitHub Copilot is moving to usage-based billing Think of it like a mobile data plan. Right now everyone pays a flat rate regardless of whether they browse Twitter or stream 4K video all day. Starting June 1, GitHub is switching to metered billing. Heavy users pay more. Light users stop subsidizing them. The mechanism: premium requests get replaced by GitHub AI Credits, billed by token consumption. Plan prices stay the same. How you pay changes. Why now? Copilot runs multi-hour agentic coding sessions across entire repos. A quick chat question and a 2-hour autonomous session currently cost the same amount. GitHub has been absorbing that difference. That stops in June. What actually changes: • Pro: $10/month, includes $10 in monthly AI Credits • Business: $19/user/month, includes $19 in credits (temporarily $30 through August) • Enterprise: $39/user/month, includes $39 in credits (temporarily $70 through August) • Code completions stay free, no credits consumed • Credits pool across the org instead of expiring per user • Admins get hard budget caps at enterprise, cost center, and user level GitHub is launching a preview billing page in early May. If you manage Copilot licenses, check it before June 1. https://lnkd.in/dxne98Z9 #GitHubCopilot #AI #Microsoft #DeveloperTools