GitHub Copilot users revolt as usage-based pricing exposes true AI costs in hours

AI costs how much? GitHub Copilot users react to new usage-based pricing system

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). How much for that prompt in the window? Spot testing by Ars Technica found that re-running our simple "build a Minesweeper game" prompt through Claude Haiku 4.5 via Copilot used about 94 credits (you can view the results here). That's a pretty decent rate for a relatively simple toy project. But it's also easy to see how those kinds of costs could balloon quickly for requests involving major changes or reviews on complex codebases. You can see that kind of ballooning cost in reports of a single complex prompt burning through 171 Copilot credits, or another spending 700 credits on "a few prompts," or a couple of Copilot-led commits using up 5,000 credits. Other Copilot users expressed surprise at just how many credits could be spent on even simple Copilot requests, from a reported 15 credits for a simple "run-of-the-mill query" to spending 100 credits in "generating a small plan." "Even though I was super cautious on the first day, trying it out with a limited number of uses, it still consumed 840 credits," one user wrote of testing Claude Sonnet 4.6 through Copilot today. "I haven't even done any really complex work yet," another user complained after reported usage representing 21 percent of their monthly Pro Copilot subscription's credit allotment in a single day. "I have a feeling I'll be going somewhere else pretty soon." Amid the pricing change, plenty of GitHub Copilot users are predictably and publicly threatening to cancel their subscriptions or looking for other AI coding options. But others say they have been able to adjust to the new world of usage-based pricing. Coder Henri Kinnunen writes that they only burned 161 credits in a "productive day" of using Claude 5.3-Codex through Copilot, thanks to limiting themselves to "very focused and deliberate changes with AI." Over on Bluesky, coder Neil Hewitt wisely noted that continuing a three-day-old chat session on Copilot probably isn't as wise now, since it means sending "the entire chat history as context every time... hey, input tokens use credits... it's not rocket science." While some Copilot users are jumping ship for other services with more generous usage limits, that kind of subsidized customer acquisition may soon give way to Copilot-style usage-based pricing across the industry. If that happens, LLMs that are more efficient with their tokens may win the economic battle; on Reddit, one user is already discussing how they've integrated Deepseek into their GitHub VSCode environment at a cost of only "about 7 cents for 15 million tokens." While you might say "you get what you pay for," some AI users are now contemplating a world where they also have to pay for what they get.

Github Copilot customers report up to 100-fold price hikes -- AI sticker shock bites as Microsoft switches to usage-based pricing

The enormous amount of money shuffling through AI's circular economy has created a money pit, and the beast therein demands sacrifices. Not too long after Anthropic shocked most of the developer world by bumping up its prices and moving Claude Code to the Max plan, GitHub Copilot has followed suit. The move from subscription to usage-based billing has left many users looking down the barrel of massive bills, according to an Ars Technica report. An ongoing discussion on the GitHub community forums includes plenty of customer testimonials, as do X posts from many different users. The overall gist is simple: many users are reporting that their bills would increase by several orders of magnitude, or that the limit is so low that a subscription plan is now either extremely limited or useless. There's even a community cost estimator that popped up a while back when the news first came to light. To wit, the AI allowance in each of GitHub's subscription plans has three tiers: the $10 Pro plan gets you 1,500 credits; the $39 Pro+ plan contains 7,000; and the $100 Max subscription nets you 20,000 credits. While it's good for Microsoft to specify precisely how many tokens each plan includes, it's worth noting that in obvious cases like long-running conversations or queries on large projects, it's exceedingly hard to estimate how many tokens any given query will use, as shown by data from a 2025 paper. Unsurprisingly, some users are reporting that even light usage, or being "super cautious", they went through significant chunks of their monthly allotment in the blink of an eye. Switching the underlying model for a query can drastically change the calculations; for example, using Claude Opus or GPT will be far pricier than using Gemini Flash. Some subscribers also warn fellow vibe-coders about resurfacing long-running conversations, as the nature of an AI bot requires the entire conversation to be re-sent again and again, quickly chewing through usage limits. Besides being more judicious about selecting the right model for a given query, some folks are experimenting with harnesses to use token-efficient models like DeepSeek to keep costs down. Those using an AI bot as an agent also have to exercise extreme caution, as there's no shortage of reports and horror stories about clankers left unchecked, racking up gigantic bills. Although there's no shortage of vitriol directed at Microsoft, as there was when Anthropic bumped up Claude's pricing, the harsh reality is that investors are growing tired of dumping money into AI companies and want to see cash inflows that are at least in the same galaxy as their expenditure. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

GitHub Copilot Costs Skyrocket As Users Are Pushed to Per-Token Billing

GitHub users who have grown accustomed to using its Copilot integration as part of their workflow are balking at cost estimates as the service moves toward per-token billing, rather than per-request billing, Ars Technica reports. The new system will charge users based on how much the AI does, rather than how many requests they make, and some users are finding their bills jumping 10x or more. For the past few years, subscription-based billing for AI has been commonplace. However, it's also been heavily subsidized to encourage adoption and obfuscate the financial costs of AI. In 2026, as AI agents drive AI usage, platform providers and AI developers are demanding more for their services. Anthropic moved to token-based billing for Claude Enterprise subscribers in April, and Microsoft did the same for GitHub Copilot this week. The GitHub switch only happened yesterday, and already, users are concerned about how fast they're burning through their credits and how much their token may cost by the end of the month. One X user blew through over half their monthly credits in one day. Another complained on GitHub's community that, where a typical month would see them use just 60% of their credits, they managed to use almost 20% in the first day under the new system. Another X user said that their entire monthly token budget was used up in less than half a workday, while another was more bullish about the move, but still used up over 70% of their credits on day one. Other users have leveraged GitHub's estimation tool to examine their typical usage and costs, and how they compare under the new system. One user previously used $39 a month, but could now be expected to receive a bill for almost $1,800 a month. Some say they will move to alternative tools like Deepseak v4. Others have suggested it's possible to adjust their workflow accordingly, deliberately using AI in a "very focused" way, Ars notes. Whether users have to change their approach or switch the AI they use, though, it seems clear that the wild west of low-cost Frontier models from the major developers may have come to an abrupt end. How that affects all the big IPOs for these major companies just over the horizon remains to be seen.

Angry devs vow to flee GitHub Copilot as metered billing takes hold

Developers seem to hate Microsoft's new usage-based billing policy for GitHub Copilot as they report burning through a month's worth of credits in hours. "This is a staggering shift from a 'predictable subscription' to a 'stressful meter-based' service that hinders my productivity rather than helping it," wrote one developer on GitHub's user forum who said they were paying for Microsoft's $39-per-month Copilot Pro+ plan but burned through about 8 percent of their monthly AI Credits allocation in two hours under the new billing system. "At this rate, my 7,000-unit quota will be depleted in less than two days." Their outrage is a consistent and growing theme among the business users of AI who suddenly see eye-popping bills after years of experimenting with a nearly free service. One GitHub Copilot developer requested a single change to their project and burned more than $6, they wrote. "Not after a day of usage. Not after dozens of prompts. After ONE request," the developer stated on GitHub's user forum. "I understand that large projects require context, but this level of consumption feels completely unreasonable and impossible to predict. How are individual developers supposed to budget for this when a single feature request can consume such a large portion of the monthly allowance?" The changes went into effect across the site on Monday. In GitHub's April post announcing the new billing scheme, Microsoft said the change was made from monthly billing to usage-based because GitHub Copilot is "not the same product it was a year ago." "It now powers far more complex, agentic workflows that consume far more compute. This change is designed to deliver a more sustainable and reliable product experience by aligning pricing to actual usage and costs," the post to its user community reads. "We believe GitHub Copilot remains the best value and experience for agentic coding. Usage-based billing aligns cost more closely to actual usage and value, while continuing to offer developers the freedom to choose the models and agents that work best for them." GitHub Copilot lets developers access a range of AI models from within their development tools. That had allowed some users to make large numbers of requests across multiple models while paying as little as $10 per month for Copilot Pro, or $39 per month for Copilot Pro+. Now, each request from users is dynamically priced depending on the model used, the request, and the amount of material submitted by the user, as well as the complexity of the answer returned. "Woke up to the new billing UI this morning. Figured I'd test it out on some actual work -- just needed Claude 4.8 to help fix a couple things on a site I'm editing," one Reddit user posted. "It gave some pretty mediocre suggestions. Didn't really solve the problem, I still had to do most of the work myself ... Then I checked the actual usage page. 1,180 credits used. 16% of my monthly Pro+ allowance. Gone. For basically nothing." The comments online have been overwhelmingly negative, with users on GitHub's forum and Reddit vowing to abandon the product and move their work directly to Anthropic, OpenAI, and some creating their own workarounds through a series of free or cheaper AI vendors, like RooCode, LM Studio, or OpenRouter. "I've opted to stick to Pro+, burn through my allocated credit in a week, and then pivot to using OpenRouter for the remainder of the month," one user posted. "OpenRouter offers a similar set of advantages that Copilot has over other providers. It can be used within the same VS Code interface. Plus it has more models and credit rolls-over for up to a year." The Register asked Microsoft about the user complaints and a GitHub spokesperson responded with a statement saying it had introduced a new billing policy, and provided a link to a FAQ. "Usage-based billing is now in effect. Pricing for GitHub Copilot now reflects actual usage with spending limits, usage dashboards, and model selection available to help manage costs. We're also introducing Copilot Max for users who need more capacity," the statement reads. ®

GitHub just switched Copilot to metered billing, and developers are watching months of credits vanish in a single day

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. Bottom line: GitHub's move from flat-rate "requests" to metered usage is forcing many developers to confront something they had largely ignored: how many tokens their everyday coding habits consume and what that usage actually costs. As the new credit-based pricing exposes the expense of long chats, large context windows, and frontier models, many are rethinking how - and how often - they rely on AI in their day-to-day work. Back in April, the company said it would move all Copilot plans to a usage-based system that bills users based on actual AI consumption, measured in tokens, starting June 1. Under the old setup, subscribers worked from a pool of "requests" and "premium requests," whether they were asking a quick question or letting Copilot grind away for hours on a complex refactor. GitHub said that model meant the service was absorbing "much of the escalating inference cost" from heavy users. That cross-subsidy is now over. Instead, users are faced with a meter tied directly to the size of their prompts, the length of Copilot's responses, and, crucially, the model they choose. Credit: twhoff / Reddit On paper, the new pricing structure looks simple enough. Each paid plan comes with a bundle of AI credits, with one credit representing one cent of usage. The $10-per-month Pro tier includes 1,500 credits, or $15 worth of AI usage. Pro+ costs $39 per month and includes 7,000 credits, while the top-tier Copilot Max plan costs $100 and comes with 20,000 credits, equivalent to $200 in usage. The catch is that those credit pools can disappear at dramatically different rates depending on whether users stick to lightweight models or rely on the largest and most expensive ones. That disparity becomes clear when comparing models. One million output tokens from a smaller OpenAI model such as GPT-5.4 nano costs about $1.25 through Copilot. The same volume generated by the frontier-class GPT-5.5 costs roughly $30. For developers who typically use the default settings, that difference was easy to ignore when everything consumed a single premium request. Under usage-based billing, however, the same "let's see what it does" approach can burn through a month's worth of credits in just a few sessions. The impact is already visible in figures users are sharing. A simple "build a Minesweeper game" prompt run through Claude Haiku 4.5 via Copilot consumed about 94 credits. For a toy project, that may seem manageable. But when users move from toy projects to production workloads, consumption can rise quickly. One person reported a single complex prompt consuming 171 credits. Another said that "a few prompts" used up 700 credits. In one case, a couple of Copilot-driven commits consumed 5,000 credits - a full quarter of Copilot Max's monthly allowance. Even ostensibly routine work is proving more expensive than some developers expected. Users have complained about spending 15 credits on what they describe as a "run-of-the-mill query" or 100 credits to generate a small plan. One user said they were "super cautious on the first day," limiting their experimentation with Claude Sonnet 4.6, yet still spent 840 credits. Another, after watching 21 percent of their Pro credits disappear in a single day, concluded: "I have a feeling I'll be going somewhere else pretty soon." Some users are treating the new pricing model as a nudge to tighten up their workflows. Developer Henri Kinnunen said they used only 161 credits during a productive day by making "very focused and deliberate changes with AI" while using GPT-5.3-Codex. Others are revisiting long-running habits that made sense when token usage was effectively invisible. On Bluesky, developer Neil Hewitt pointed out that keeping a three-day chat thread alive means sending the entire conversation back as context with every request. Those past messages all count as input tokens, and input tokens now have a direct cost. As he put it, "input tokens use credits... it's not rocket science." The backlash has prompted some users to explore alternatives with less aggressive pricing, at least for now. One developer described integrating DeepSeek into a GitHub and VS Code workflow and estimated the cost at "about 7 cents for 15 million tokens" - a figure that illustrates just how wide the pricing gap can be between providers and models. At the same time, there is a growing sense that Copilot's move may not remain an outlier for long. If other AI coding assistants follow the same path, the era of flat-fee, "all-you-can-eat" access could be coming to an end. For developers, that shifts the conversation from "What can this model do?" to "What is this task worth?" Token efficiency, context management, and model selection - once abstract concerns - are becoming operational decisions with real budget implications. The challenge is no longer just getting the best answer, but getting an answer that is good enough without quietly burning through next month's AI budget in the process.

Microsoft switches GitHub Copilot to usage-based AI token billing

Microsoft will transition its GitHub Copilot billing from a flat subscription rate to a usage-based token model starting June 1. This new system will charge users according to the tokens consumed during use, which is a shift from the previous low flat rate based on requests. Smaller companies and individual developers are expected to see significantly higher costs, raising concerns about budgeting for these increased expenses. Criticism has emerged on social media platforms such as Reddit and X, where some developers have reported sharp increases in their monthly costs. One Reddit user claimed their expenses would rise from around $29 to nearly $750 monthly under the new model. Another user indicated their costs could skyrocket from approximately $50 to about $3,000, a figure that many have deemed exorbitant. In response, some users contended that those facing high costs might lack sufficient development knowledge, arguing that efficient use of Copilot could keep expenses manageable. Critics highlighted that the rising costs seem extreme. One comment suggested that users who are consuming excessive tokens are often "vibe-coders," relying on trial and error rather than solid programming skills. "The vast difference between some of us working all day and still barely having overage... It's pretty affordable for even small outfits if used as a tool," a user noted. Concerns regarding the previous billing model have also surfaced, with questions about the significant losses incurred by Copilot under the flat rate system. One Redditor queried how much money the service was losing, hinting at unclarity in the financial aspects of GitHub Copilot. Discontent among developers reflects a view that Microsoft has changed its approach after previously encouraging users to exploit the chatbot's capabilities. "The only one at fault here is Microsoft. They provided this billing method and kept making it easier and easier to burn through massive numbers of tokens," a user commented.

Github Copilot's New Tokenised Billing Inflates AI Billing for Vibe Coders

The AI coding assistant has moved to a usage-based pricing model from this month instead of a predictable subscription-based system that developers were paying thus far Microsoft's Github Copilot users in the small enterprises segment may end up paying based on how much AI computing power they consume. The AI coding assistant has moved to a usage-based pricing model from this month instead of a predictable subscription-based system that developers were paying thus far. So, it is bye-bye to fixed monthly fee for access with usage now depending on how much compute power the user consume. And users are discovering that AI just got expensive than what was expected earlier. "Instead of counting premium requests, every Copilot plan will include a monthly allotment of GitHub AI Credits, with the option for paid plans to purchase additional usage. Usage will be calculated based on token consumption, including input, output, and cached tokens, using the listed API rates for each model," says a blog post by Github. To help customers prepare, we are also launching a preview bill experience in early May, giving users and admins visibility into projected costs before the June 1 transition. This will be available to users via their Billing Overview page when they log in to github.co From now on users will be charged based on the number of tokens they burn through while working instead of a low flat fate based on requests. The developer community in general aren't too happy with the new system and have taken to social media platforms to discuss the drastic cost escalation. While a user claimed that they ended up consuming 60% of their quota in a month while under the new system 25% was finished within a day itself. Others cribbed that even small coding tasks appeared to consume large credits. Yet another user claimed that a small task taking less than 30 minutes with one prompt to refine an existing change proposal ended up wiping away 16% of their tokens at one shot. Users on Reddit shared widely varying expense figures that they may incur due to this changeover. These numbers varied from $600 a month to over $5,200. Such was the impact of these random estimates that another section of users quoted these numbers and expressed concerns that the reality over long-term affordability of AI coding tools was exposed. In fact, a Redditor headlined the post with "Bye Bye Copilot - New pricing looks like a joke" and went on to share that their billing grew from just $29 a month to about $750. "This new usage model is just stupidly expensive," the user said while announcing that they plan to adjust their billing by cancelling. However, Github thinks that all's fair. This change aligns Copilot pricing with actual usage and is an important step toward a sustainable, reliable Copilot business and experience for all users, the blog said while noting that they're launching a preview bill experience to provide customers a support experience for the changed terms of usage. Of course, the flip side of all this criticism over high costs comes from another set of users who wryly point out that Copilot users should not be complaining as if they actually knew what they wanted to code, they shouldn't be burning up some many tokens so fast. "These folks are probably vibe-coders with little actual development knowledge," they quip. Having said so, it hasn't been easy to figure out the costing behind Copilot and the money that Microsoft may be spending to subsidise the vibe-coding frenzy. Given that its userbase is a mystery and largely hidden from public gaze, makes things tougher to comprehend, beyond the obvious fact that pay-as-you-use is the only revenue model that the industry knows. Once again Copilot has a different view. Asserting that it wasn't the same product it was a year ago, the post notes that it evolved from an in-editor assistant into a agentic platform capable of running long, multi-step coding sessions, using latest models, and iterating across entire repositories. "Agentic usage is becoming the default, and it brings significantly higher compute and inference demands," Github has said. Now a quick chat question and a multi-hour autonomous coding session can cost the user the same amount. GitHub has absorbed much of the escalating inference cost behind that usage, but the current premium request model is no longer sustainable, said the company highlighting what could be the future of AI. Usage-based billing fixes that. It better aligns pricing with actual usage, helps us maintain long-term service reliability, and reduces the need to gate heavy users, Github says. In the ultimate analysis, some users have criticised the changes while others have criticised the original critiques. However, one common grouse among both these types of users is the fact that Microsoft first encouraged users to indulge with the chatbot indiscriminately, and are now asking them to pay a fortune for using it. Looks like the unit economics has kicked in and possibly kicked out the golden age of Github Copilot.