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Something is hilariously off here: Why should I pay $10 and be forced to use it by the end of the month, while I can pay $10 and have it last as long as I want?

Their "API pricing" is exactly the same as that of providers: https://docs.github.com/en/copilot/reference/copilot-billing...

I'm thinking the same. Downgrade to Pro and use OpenRouter (same price) for overage.

Seems a massive loss for Microsoft. Presumably there's a further rugpull to come.

I have to wonder if it's because of how many Enterprise customers they have who have standardized on Github Copilot and gotten it through the gauntlet of legal approvals etc.
I'm wondering if they're basically saying they're going to give $10/month free API credits to students and open source maintainers and so on... while otherwise getting out of the consumer portion of this space.
for my experience currently, I greatly prefer the VSCode Copilot extension experience over the Claude Extension

I think VSCode only supports copilot for "autocomplete" too

on top of that, you need GitHub Copilot for the PR reviewer functionality in GitHub

Enterprise gets pooled credits and will like having everything go through one place so I think it still works.
I am a bit confused by the separation between VSCode and Copilot. If I cancel my Pro+ subscription, can I still use Copilot with my own OpenRouter key?
Is there a way to use the autocomplete feature with an api?
is $10 Pro monthly subscription a pre-requisite before i can purchase $10 in API credits?

PS: i would have loved if I can directly buy $10 in credits and be free to spend it as quickly or as leisurly as I want -- without any monthly expiry or fixed recurring payments

kilocode allows you to keep your credits at the end of the month, and if you run out, give you an extra 50% I think.

(No affiliation, they're my next stop when my trial of copilot runs out).

The era of subsidised inference is truly ending. The new model multipliers (https://docs.github.com/en/copilot/reference/copilot-billing...) seem like a huge leap, though. From 1x to 6x for new-ish GPT and Sonnet models. 27x for Opus...

Seems like folks would be better off with OpenRouter instead.

"Your plan pricing is unchanged: Copilot Pro remains $10/month and Pro+ remains $39/month, and each includes $10 and $39 in monthly AI Credits, respectively."

If there's no discount on credits (in terms of tokens per dollar) over other providers, I'm going to switch to a PAYG provider. If there's a month where there's little to no coding I can pocket the 10$. What incentive do they give to stay with this plan?

Well.

Just got an email from GitHub saying they'll be raising prices for Co Pilot.

"To keep up with the way you use Copilot, we're transitioning to usage-based billing, and we want to give you enough time to prepare."

Man, it was fun. Having my tokens subsidized by Microsoft. If the prices go up to much I guess I'll try Deepseek again.

Everybody who says it's a 5-9-27x seems to not be aware of the obvious loophole. More like 50x increase. You were able to use over $500 worth of Opus on a $10/mo Github plan easily, no hacks. You could just prompt "plan this out for me, don't stop until fully planned, don't ask any questions", and you would get ~$5 worth of planning in one 3x request. At 100 requests/mo, each easily reaching $5, that's easy $500 worth of tokens.
"Plan prices aren’t changing.”

Isn't this like saying "The Porsche you rented at $200/mo is now a Honda. But the price hasn't changed!"

I was curious why a company would still use the VS Code + Copilot sidebar method for coding, rather than something like Claude Code. Turns out there’s a GitHub Copilot CLI!

I thought I was pretty familiar with available options, but no one in my circles ever mentions this product. It doesn’t seem to have much mindshare.

Has anyone used it? What’s your experience?

https://github.com/features/copilot/cli

I don't use Copilot or any paid AI but all of this usage-based billing reminds me of cellphones back when you paid per individual text message.

Usage paying for AI is 1000x crazier because you're not even getting a guarantee in the thing you pay for in the end. You have to keep feeding it prompts and hope it gives you the solution you want. You may end up with no expected result yet you are paying for it. At least with texting, you got what you paid for.

I wonder how long it'll be before all AI costs are flat unlimited monthly fees or even free across the board, without compromise.

Windsurf made a similar change in March: https://docs.windsurf.com/windsurf/accounts/quota

> In March 2026, Windsurf replaced the credit-based system with a quota-based usage system. Instead of buying and spending credits, your plan now includes a daily and weekly usage allowance that refreshes automatically.

With hindsight, per-request pricing makes no sense at all if an agent can burn a widely varying amount of tokens satisfying that request. These pricing plans were designed before coding agents changed the dynamics of token usage.

I wonder if GitHub (Microsoft) is implicitly betting that enterprise demand is sticky enough to absorb these rates, especially given that Opus 4.6 “fast” was being listed at a 27x multiplier. Maybe they saw enough usage at that price point to conclude the demand is real. Or maybe the strategy is to keep the enterprise customers who can justify it while shedding heavier individual and power-user usage.

The interesting question is how long it takes enterprises to notice the capability/pricing tradeoff, and whether they respond by limiting access to the strongest models internally.

The part that worries me is that this market is still very early. Most developers and organizations are still learning how to use these tools effectively. Raising the experimentation cost this much may slow down the discovery process that makes the tools valuable in the first place.

Github had, by far, the most easily game-able agent usage policy. People would force the agent to run a script before the end of turns that consisted entirely of `input("prompt: ")` so that you could essentially talk endlessly to an agent for the price of a turn. I see this less about the future of this industry and more about fighting the costs incurred by bad actors.
There is noticeable trend across all agentic coding platforms that this situation is no longer sustainable.

With this kind of pricing (sonnet 4.6 has 9x multiplier, previously 1x) it begs the question why use Copilot to begin with.

You could easily just buy the tokens directly and have a lot more choice as well.

I liked copilot because I didn't have to think about tokens. I get hung up when having to think about the price of things, and its hard to think about the project at the same time I got to think about token usage like a gas bill. The usage system had its own issues, but having a set amount of requests was a very comfortable way to use a paid AI service.
So given that I primarily interact with LLM's through VSCode, and I prefer the Copilot interface to the Claude Code plugin, does anyone have any suggestions on other plugins I should try? In my experience, Copilot is much more "plugged in" than any of the other plugins, in the sense that it can see things like linter outputs in VSCode. Basically, copilot "sees what I see" in a way that no other plugin or command line tool can, which make it much more ergonomic to use.

With this pricing change, I see no reason at all to stick with Copilot in principle, but I really need to solve this issue of IDE integration to move on.

Has anyone found the answer to this yet?

> What is the benefit of using the Copilot Pro+ at 39$/month instead of using the Copilot Pro at 10$/month and paying for extra usage?

Cancelling. Going with Codex $100, Kimi annual plan, DeepSeek API, and a local LLM once I get a Mac Studio.

Inference economics are going to be brutal in 2026 H2 when DeepSeek's new infra and model improvements come online, and Kimi launches K3. By brutal, I mean for OpenAI and Anthropic.

What's the current situation for coding with Local LLM's on decent hardware? I have an M3 Max with 64 gb of ram and am thinking I should start looking at Ollama and Opencode? Is this a useful stack for smaller personal projects?
After seeing the ridicolous multiplier increase I've added a calendar event to cancel my subscription mid-May.

(I'm a copilot subscriber since 2022)

Current multipliers vs from June

  Opus 4.6  3x -> 27x
  Opus 4.7  3x -> 27x
  GPT  5.4  1x ->  6x
EDIT: only applies to annual plans
I was surprised to find that this sentence

> Plan prices aren’t changing

did not continue with an em-dash followed by something profound that is changing.

Plan prices aren't changing -- the value you get out of it is.

The cheapest copilot plan felt totally unsustainable to me. For around £8 month i was getting 100 opus 4.6 prompts (albeit with a reduced context window size around 128k iirc vs 200k to 1m for first party hosted opus). Gpt5.4 was hosted with 400k context iirc.

On top of that, you’ve got 2000minutes of container runtime, so running cloud agents was included. As was anthropic agent sdk mode via copilot which is very comparable with claude code - not identical, the anthropic “modular prompt” is much leaner in the sdk version.

I cant say im mad, i got above what i paid in value. That said, going forward ill probably go back to openrouter payg rather than a subscription.

I got a free 3months of the gemini £19 plan and ive been playing quite a bit, 3.1 pro is a good model, i just find it slow. Flash i think i under appreciated until now.

I pay for Copilot annually, and mostly for its code auto completion features. I use CC if I want to do anything agentic. Not sure if I want to pay more for occasionally-good-intellisense at this point.
How is this legal when people paid for a yearly plan in advance?
They're not the only ones in the AI sphere to wind back, but they're the weirdest case in my eyes. Microsoft invests in having engineers building open models and they don't use a single one. I really don't get it.

But what really surprised me most about Copilot is that it would bill you per question, nothing about tokens. So if I managed to produce a prompt that gave me back an insane amount of tokens for something, which using any Claude model would easily accomplish, you were giving me my money's worth, at your own expense. The math is not gonna math out forever.

After 2 months of using copilot pro, they've charged us 22$ in premium requests for my user, i spend roughly 1900$ in tokens, going of the on-demand pricing. This is estimated to be around 40-60% of real costs. They are undercharging by a factor 50 to 90!

This is just the start of the rug-pull

It begins.

"It" being the end of subsidization of tokens and plans (expected) but while lock-in to foundational models and cloud services is still lacking. Guess investors want their ROI sooner than later, given how big of a wrench the AI boom has thrown into global economics.

I bought a copilot subscription for some small personal projects at Christmas.

I haven't been able to use my subscription much over the busy spring months, but i'm being charged every month.

I'd be tempted to keep the subscription if usage-based billing meant that i'd save money when i had less time.

But today, after hearing this, i cancelled my subscription.

This subsidized inference is just a marketing ploy to increase prices and profit.

If common people can have a DIY setup with an open source model cheaper than those behemoths with a scale advantage, it's clear that we have been played.

Time to either self host a Chinese open source model or to just pay the cheap Chinese providers.

This marks the beginning of the end of the AI free money era. Next they will dramatically raise prices when they have to be profitable on tokens.
So I guess from now on GH Copilot is only worth it if you want a quality autocomplete in VSCode.
The 27x multiplier on Opus is the tell. That is not a pricing model designed for broad adoption, it's a price signal that says 'use the cheaper model.' The problem is that once users start self-censoring which model they reach for based on cost anxiety, you've degraded the product experience in a way that's invisible in the metrics but very visible in churn.

Flat subscriptions had one big advantage: zero cognitive overhead per request. That's worth more than people admit.

Does this mean you can only prompt "Hello" every morning for a month with Opus 4.7 ?
some of Github's open source maintainers have lost their free github copilot pro, guess this is really the next step for them to save cost in their infrastructure.
I really don't understand why OpenAI, Anthropic and Microsoft are in competition to see which one of the three will elevate deepseek the most.
I'm not sure I understand this. All I know is now, I pay $39/month (actually less because I paid a year up front), use the agent, mostly on auto--and only choosing a model if it got stuck or in a loop--every day, and haven't hit any limits yet. It seemed to good to be true, after hearing others talk of $300/month bills. I guess it was.
I started to use github copilot with vscode, but have never been too happy about the system. Over the months I gravitated to much more agentic workstyle, hardly ever editing much code by hand. The vscode IDE was getting more in the way. I had already started to look at OpenCode, and when I found it has a web interface, I was happy to switch over. I use a simple editor (KDE's Kate), or just less to skim through the code and/or a git diff. OpenCode has some free models in it, but I think I will need to get some kind of subscription for a better one. But it won't be copilot any more. The market is moving so fast that I don't know what are the most resonable models, or the most flexible way to set them up so I can switch when prices change yet again.
Whose idea was this “premium request” model anyway? If you’re going to invent a new metric used to bill, why not align it with what, even at the time, was a clear underlying cost structure that GitHub actively chose to ignore for a more confusing system.
Are you telling me that inference costs did not go down, as the AI crowd keeps preaching?
I'm happy I invested in local solutions and cutting context to the bone for API providers. Claims about AI being able to fully replace programmers never took into account the long-run equilibrium price of inference.