Key Findings
GitHub Copilot Fusion reduces the average cost per task to $5.59, compared to $11.42 for Claude Code running Anthropic’s Claude Opus 5.5 at its Max setting. According to Artificial Analysis, Fusion Max scored 60 on the Coding Agent Index v2.0, trailing Claude Code’s 62 by only two points. Additionally, GitHub reports that Fusion Max completed benchmark tasks in approximately 40% less time than the Claude Code configuration.
Technical Details
Fusion is an orchestration engine rather than a standalone AI model. It evaluates tasks involving reasoning, debugging, code generation, and tool use to determine the optimal routing. It utilizes a pool of models including GPT-6 Astra, GPT-6 Sol, Claude Opus 5.5, and Claude Sonnet 5.5. Users can select from three reasoning effort levels: Standard, High, and Max.
The system employs three specific execution patterns:
- Single: Sends the task directly to one model.
- Cascade: Starts with a low-cost model and escalates to a stronger one if necessary.
- Critique: One model drafts a response, a second reviews it, and the first revises the output.
Background & Context
Unveiled at the GitHub Universe conference on October 28, Fusion incorporates research from Project HydraFusion. While Microsoft CEO Satya Nadella mentioned potential savings of up to 77% based on company evaluations, the Artificial Analysis data specifically highlights a reduction in token use; Fusion used 7.2 million tokens per task, roughly half that of the Opus 5.5 Claude Code configuration.
Significance & Outlook
The system shifts the focus from the price of individual foundation models to the total cost of completed tasks. While Fusion led on Terminal-Bench 4.0 with a score of 71, it trailed Claude Code (56) and Devin Fusion (54) on the FrontierCode repository changes evaluation, indicating that performance varies by assignment type.
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