GitHub Copilot‘s Pricing Pivot: A New Era of AI Coding Costs
GitHub Copilot just made a big move. The billing model switched from the old request-based system to a usage-driven one with AI “credits.”
This change has some real consequences for developers. Now, even routine coding can rack up surprising costs, and that’s got people talking about whether AI tools like this are sustainable or even efficient in the long run.
Understanding the New Credit System
Back in April, Copilot started rolling out its new billing structure. As of this week, it’s fully in place—no more request-based pricing.
Developers now get monthly buckets of AI “credits,” each worth $0.01. There are a few plan options:
- Pro: $10/month for 1,500 credits.
- Pro+: $39/month for 7,000 credits.
- Copilot Max: $100/month for 20,000 credits, sometimes with bonus credits thrown in.
Here’s where it gets tricky. The number of credits you burn through isn’t fixed. It depends on how many input and output tokens your prompt uses, and which Large Language Model (LLM) you pick.
So, if you use a more complex model or a longer prompt, you’ll pay more. The cost can swing pretty wildly from one interaction to the next.
The Sticker Shock and User Reactions
Since this change, a lot of users have been blindsided by the new costs. What used to be a simple “request” can now chew through most—or all—of your monthly credits, sometimes after just a day of heavy coding.
People are sharing stories online. Some say basic prompts cost 15 to 100 credits. Harder coding tasks? Those can eat up hundreds or even thousands of credits. A few users even calculated that their old usage would now cost thousands of dollars a month. That’s wild.
We tried it ourselves, similar to what Ars Technica did. Generating a Minesweeper game with Claude Haiku 4.5 took about 94 credits, which honestly feels high.
There’s a big difference between models, too. GPT-5.4 nano is a lot cheaper per token than GPT-5.5. So, picking the right model can really affect your bottom line.
Adaptation and the Future of AI Coding
Developers are scrambling to adjust to these new costs. Many have started constraining their interactions with Copilot.
They’re making a point to keep chat histories short, since long ones eat up more tokens. Folks are also switching to efficient models that give better results for the money.
But for some, the price hike is a dealbreaker. A few have said they’ll cancel their subscriptions or try out other, maybe cheaper, AI coding assistants.
This whole pricing shakeup from GitHub really exposes how much heavy Copilot users were getting subsidized before. The industry keeps running up against the same dilemma: Do you chase advanced model capability, or worry about the rising inference cost?
If usage-based pricing becomes the norm, token-efficient models could have a real edge. Maybe that’ll push more folks toward tools that squeeze more value out of every credit.
Here is the source article for this story: AI costs how much? GitHub Copilot users react to new usage-based pricing system