GitHub Copilot Users React To New Usage-Based Pricing System (arstechnica.com) 11
An anonymous reader quotes a report from Ars Technica: In April, GitHub announced that it was moving subscribers from request-based billing to a usage-based model for its AI-powered Copilot service. As that new pricing model goes into effect today, many GitHub Copilot users are reporting some extreme sticker shock as they realize just how quickly their previous "normal" usage is burning through their newly limited monthly allotment of AI credits. Across social media and forums, many Copilot users are sharing personal statistics showing how just a few hours of AI usage can now account for a large chunk of their new monthly subscription caps. For some users, it reportedly took less than a day to use up a month's usage quota.
That's a big change from previous months, when GitHub Copilot subscribers were allocated a certain number of "requests" and "premium requests" based on their payment tier. GitHub said that the old system meant that "a quick chat question and a multi-hour autonomous coding session [could] cost the user the same amount," forcing Copilot itself to "absorb much of the escalating inference cost behind that usage." [...] Indeed, some Copilot users have been sharing estimates from GitHub's own tool showing that their previous monthly usage would rack up bills in the thousands of dollars under the new pricing plan. Under GitHub's new usage-based pricing system, paid Copilot subscriptions instead grant users a certain number of AI "credits" each month, with one credit corresponding to $0.01 of usage. Subscribers also get bonus credits depending on their subscription level: the $10/month Pro plan includes 1,500 credits ($15 worth); the $39 Pro+ plan includes 7,000 credits ($70 worth); and the $100/month Copilot Max plan includes 20,000 credits ($200 worth).
The precise number of Copilot credits used by a given prompt is determined by the number of input and output tokens used and the rates charged by the underlying large language model. That means pricing is highly dependent not just on the type of request but on the specific model that a user chooses. One million output tokens from OpenAI's GPT-5.4 nano would run just $1.25 on GitHub Copilot, but that same level of output would run $30 on the frontier GPT-5.5 model (Copilot users who rely on "Auto" mode to pick the most appropriate available model for any request should be extremely careful, as some users report it can switch to expensive models for extremely simple queries).
That's a big change from previous months, when GitHub Copilot subscribers were allocated a certain number of "requests" and "premium requests" based on their payment tier. GitHub said that the old system meant that "a quick chat question and a multi-hour autonomous coding session [could] cost the user the same amount," forcing Copilot itself to "absorb much of the escalating inference cost behind that usage." [...] Indeed, some Copilot users have been sharing estimates from GitHub's own tool showing that their previous monthly usage would rack up bills in the thousands of dollars under the new pricing plan. Under GitHub's new usage-based pricing system, paid Copilot subscriptions instead grant users a certain number of AI "credits" each month, with one credit corresponding to $0.01 of usage. Subscribers also get bonus credits depending on their subscription level: the $10/month Pro plan includes 1,500 credits ($15 worth); the $39 Pro+ plan includes 7,000 credits ($70 worth); and the $100/month Copilot Max plan includes 20,000 credits ($200 worth).
The precise number of Copilot credits used by a given prompt is determined by the number of input and output tokens used and the rates charged by the underlying large language model. That means pricing is highly dependent not just on the type of request but on the specific model that a user chooses. One million output tokens from OpenAI's GPT-5.4 nano would run just $1.25 on GitHub Copilot, but that same level of output would run $30 on the frontier GPT-5.5 model (Copilot users who rely on "Auto" mode to pick the most appropriate available model for any request should be extremely careful, as some users report it can switch to expensive models for extremely simple queries).
Should get really exciting. (Score:3)
So long as they were losing money hand over fist the vendor does want to throw enough tokens at you to make you feel like you are having a good time; but as few as are required to do that since they lose money on every one. If they were breaking even or turning a profit the incentive would be to sneak as much spend and upsell in as possible; and it's well known that the verbosity/cost of LLM chatter is hard to predict; harder if there are multiple models and other complications being switched around in the background.
What sort of exciting little tricks will we see from vendors who actually make more if you use more?
True cost of AI LLMs (Score:2)
Hopefully AI thing will start to cool a bit now that the free ride is over and end users start to bear the full cost of these systems. Up until now the big AI companies have been giving it away at a token cost to keep the hype going.
Hopefully seeing the true costs will push demand more towards more efficient, smaller, specialized local models for many applications.
Re: (Score:2)
"Cool a bit"? If the general truth about the subsidizing of prices gets out, we are looking at a big bubble burst at least as bad as the dot-com poppage.
Investor funds and market-share-fights have kept AI prices low or free, but of course that can't last forever. I suspect one prominent but stressed AI company will spill the beans about fake pricing ("we all do it!"), putting pressure on the rest to prove that claim is false, which they'll fail, spooking investors, ending the run, and triggering a recession
Turn off automated PR reviews (Score:2)
I'm disabling all automatic PR reviews for sure. I was going to do this anyway, but it was a setting the org controlled so I didn't have a choice. Now I think we have an argument for ending Copilot's review feedback. Because while the models are fine at reviewing code, mostly, the Copilot tool itself is garbage.
Post Customer Acquisition (Score:2)
Now who is surprised that prices go up after the customer acquisition phase?
Memory and compute are expensive. Data centers are aren't as easy to build as once thought. [finance-commerce.com]. Power is expensive. People fights over land and water rights.
And if the rest of the pack like Claude [theregister.com] moving to usage based limits. Then might as well make the change, Microsoft isn't a startup which is burning investor cash. They are definitely going to make a profit. AI ain't cheap and they already have the customers.
Re: (Score:2)
Now who is surprised that prices go up after the customer acquisition phase?
Like all drug dealers, the first hit is always free.
They should have waited until more jobs were eliminated and companies were more dependent on them.
I switched to Cursor AI after Copilot rolled out the 300 request cap. It is vastly superior overall, and whatever type of account my company provides, I've yet to hit a usage limit.
So long and thanks for all the circular funding (Score:2)
Let's recap. First, VC and mega-tech corporate coffers were the sources of unlimited funding. Compute was bought and essentially offered free or nearly free to even the most voracious users to juice usage stats and hopefully disrupt that too-long-entrenched habit people have of, let me check my notes, "using their brain to think." And to do 30% of the job of a person at 5% of the cost, sure, why not! Four to six months ago, those funds started drying up.
Fortunat
Alternatives (Score:2)
If AI services are becoming too expensive in the current environment, we can look to nature for help. There is a an abundant species of large mammals in the ape family that can be trained to do this kind of work as well.
Re: (Score:2)
Reminds me of The Feeling of Power [wikipedia.org] by Isaac Asimov.
Well, that's a shock. Not. (Score:2)
It's the classic enshittification cycle, also beloved by drug-dealers.
1. Get users hooked on free or cheap service.
2. Once they're hooked, jack up the price.