惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

V
V2EX
博客园 - 叶小钗
Last Week in AI
Last Week in AI
Google DeepMind News
Google DeepMind News
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Microsoft Security Blog
Microsoft Security Blog
腾讯CDC
P
Proofpoint News Feed
大猫的无限游戏
大猫的无限游戏
The Cloudflare Blog
aimingoo的专栏
aimingoo的专栏
月光博客
月光博客
量子位
A
About on SuperTechFans
Engineering at Meta
Engineering at Meta
Apple Machine Learning Research
Apple Machine Learning Research
Jina AI
Jina AI
博客园 - Franky
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
人人都是产品经理
人人都是产品经理
D
DataBreaches.Net
博客园_首页
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Stack Overflow Blog
Stack Overflow Blog

InfoWorld

AWS boosts CloudWatch Logs query limits by 10x to ease debugging for developers, SREs 21 LLMs tuned for special domains The new AI lock-in AWS adds Advanced Prompt Optimization tool to Bedrock Capacity markets could reshape cloud computing Four cutting-edge tools for spec-driven development Anthropic puts Claude agents on a meter across its subscriptions Notion courts developers with a platform for AI agents and workflow automation Using continuous purple teaming to protect fast-paced enterprise environments A better way to work with SQL Server Evidence-driven workflows: Rethinking enterprise process design AWS debuts Graviton-powered Redshift RG instances to cut analytics costs SAP’s AI promises last year? Most are still rolling out First look: Lemonade serves up local AI with limitations GitLab CEO sees developer tool bill increasing 100-fold Red Hat adds support for agentic AI development What’s new and exciting in JDK 26 Kill the loading spinner with local-first data and reactive SQL A networking revolution at AWS Tokenmaxxing is super dumb Hands-on with React, Supabase, and PowerSync How to add AI to an existing product (without annoying users) Your AI doesn’t need another database What happens when engineering teams reorganize around AI agents Python isn’t always easy When cloud giants meddle in markets 12 model-level deep cuts to slash AI training costs The best new features in Python 3.15 Teradata launches platform for enterprise AI agents moving beyond pilots Three skills that matter when AI handles the coding
GitHub shifts Copilot to usage-based billing, signaling a...
2026-04-28 · via InfoWorld

GitHub is moving its Copilot coding assistant to a usage-based billing model, replacing fixed subscription pricing with consumption-based charges as demand for AI-driven development workloads increases.

The change, announced in a company blog, will take effect on June 1 and will apply to Copilot Pro, Pro+, Business, and Enterprise plans. Under the new model, usage will be measured through “AI credits,” reflecting the compute resources consumed during interactions with the service.

“Today, we are announcing that all GitHub Copilot plans will transition to usage-based billing on June 1, 2026,” Mario Rodriguez, GitHub’s Chief Product Officer, wrote in the blog post. “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.”

There will be no change to base subscription prices, and every plan will include a monthly allotment of credits matched to its price, and once that allotment is exhausted, customers can either buy more or stop, the blog post added. Token consumption will be charged at the published API rate of the underlying model.

The change marks the second pricing recalibration for Copilot in less than a year. GitHub introduced premium request limits in June 2025, capping Pro users at 300 monthly premium requests and Enterprise users at 1,000, with overages billed at $0.04 each.

It also follows a week of tactical changes. The company tightened limits on Copilot Free, Pro, Pro+, and Student plans last week and paused self-serve purchases of Copilot Business, framing both as short-term reliability measures while it stood up the new metering infrastructure. Rodriguez said those limits would be loosened once usage-based billing is in effect.

Why GitHub is changing the model

Rodriguez framed the move as a response to how Copilot is being used today, rather than a price increase.

“Copilot is not the same product it was a year ago,” he wrote in the blog. “It has evolved from an in-editor assistant into an agentic platform capable of running long, multi-step coding sessions, using the latest models, and iterating across entire repositories. Agentic usage is becoming the default, and it brings significantly higher compute and inference demands.”

Under the existing premium request unit (PRU) model, a quick chat question and a multi-hour autonomous coding run can cost the user the same amount, the post said.

“GitHub has absorbed much of the escalating inference cost behind that usage, but the current premium request model is no longer sustainable,” Rodriguez wrote. “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.”

Sanchit Vir Gogia, chief analyst at Greyhound Research, said the sustainability framing was accurate but incomplete. GitHub was managing its own inference cost exposure, he said, and the per-seat model was breaking under agentic workloads at the same time. “The first is the proximate cause. The second is the structural cause of the proximate cause,” Gogia said.

A single developer seat, he added, now contained two very different economic profiles. “A quiet user nudging completions across a normal working day. A power user orchestrating hour-long edits on a frontier model with heavy context. The first costs almost nothing to serve. The second can cost an order of magnitude more, sometimes considerably more than that.”

A market moving to consumption pricing

GitHub is not the first AI coding vendor to pivot to consumption-based pricing. Cursor moved from fixed fast-request allotments to credit pools in June 2025, prompting a public apology and refunds after some users incurred large overages. Anthropic took a similar path with Claude Code, charging on a token basis through its API with capped subscription tiers layered on top. OpenAI followed, moving Codex pricing onto token-based credits.

The shift comes as enterprise AI cost overruns are emerging as a recurring CIO concern. IDC has forecast that the Global 1,000 companies will underestimate their AI infrastructure costs by 30% through 2027, a gap that token-metered tooling will widen rather than narrow.

Gogia said the pricing convergence across vendors was a workload event being expressed through pricing, not a pricing fashion. He warned that better telemetry from vendors would not, on its own, contain the spend. “The dashboards do not lower the bill. The architecture lowers the bill. The dashboards merely describe the bill while it arrives,” he said.

GitHub is keeping its plan prices unchanged across Copilot Pro at $10 a month, Pro+ at $39, Business at $19 per user per month, and Enterprise at $39, with each plan now carrying a monthly pool of AI Credits worth the same amount as the subscription, the post added. GitHub will preview the new bills on customer billing pages from early May, ahead of the June 1 transition.