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At GitHub Universe 2026, held on October 28–29, 2026, GitHub announced that Copilot Fusion, which integrates automatic model selection with multi-model collaboration, is now generally available and can be used in VS Code, the GitHub Copilot app, the CLI, and JetBrains IDEs. The feature automatically determines which model to use according to three processing tiers—Standard, High, and Max—and employs three execution modes: Single, Cascade, and Critique. GitHub says Fusion Max scores 60 on the Artificial Analysis Coding Agent Index, within 2 points of Claude Code using Opus 5.5 Max, while costing about half as much in average API cost per task and taking about 40% less time. In the same period, the desktop GitHub Copilot app began public beta testing of Projects, which centralizes materials, repositories, conversations, and artifacts in one place for management. Follow-up reporting further explained that Fusion Standard also supports task execution by locally installed MAI Code 1.1 Flash or Qwen3.8 Flash Next models in public preview.
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GitHub officially releases Copilot Fusion, automatically combining multiple AI models based on the taskDevelopments
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- Source:gihyo.jp
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Nov 2
Publickey
GitHub officially releases Copilot Fusion, automatically combining multiple AI models based on the task
At GitHub Universe 2026, GitHub announced the official release of GitHub Copilot Fusion, a feature that selects a single AI model or a combination of multiple models to execute based on task characteristics. The original article presents three collaboration modes, one of which has a low-cost model draft a plan, a quality-check model verify it and decide whether to escalate to a stronger model, while another has models from different model families independently review the draft and lets the drafting model make one revision. The feature offers three load levels—Fusion Standard, Fusion Hight, and Fusion Max—to balance quality and cost, plus a Fusion Fast that users cannot specify; Fusion Standard also supports locally installed MAI Code 1.1 Flash or Qwen3.8 Flash Next models to execute tasks, in public preview.
Oct 30
Semiconductor Industry Observer
GitHub Discloses 7.4 Billion AI Code Commits per Month, Adding 4 Million CPU Cores in a Year
At the GitHub Universe 2026 conference, Jay Parikh, Executive Vice President of Microsoft CoreAI, disclosed that code commits on the GitHub platform grew 6x year-over-year, reaching 7.4 billion in September alone, with more than 40% of Pull Requests initiated by AI agents. To handle the traffic, GitHub added 4 million CPU cores, 160PB of high-speed storage and 50Tb/s of network bandwidth this year, and is refactoring its underlying architecture to decouple compute from storage, with peak throughput expected to increase by up to 35x. The conference also introduced Copilot Fusion, a multi-model orchestration and routing layer that dynamically distributes requests among multiple models based on task type.
gihyo.jp
GitHub officially makes Copilot Fusion available at Universe 2026, and opens public beta of Copilot…
At GitHub Universe 2026, held October 28–29, 2026, GitHub announced that Copilot Fusion, which integrates automatic model selection with multi-model collaboration, is now generally available. It can be used in VS Code, the GitHub Copilot app, the CLI, and JetBrains IDEs, and it automatically determines which model to use and which of three execution modes—Single, Cascade, or Critique—to apply, based on three processing tiers: Standard, High, and Max. The desktop GitHub Copilot app is also beginning a public beta of Projects, which centralizes materials, repositories, sessions, and artifacts in one place for management. GitHub says Fusion Max scores 60 on the Artificial Analysis Coding Agent Index, within 2 points of Claude Code using Opus 5.5 Max, while its average API cost per task is about half and its time is about 40% less.
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