GitHub Copilot Fusion orchestrates Anthropic and OpenAI models to balance performance and cost
GitHub has released Copilot Fusion in GitHub Copilot, a runtime orchestration system that selects and coordinates models from Anthropic and OpenAI, including Claude Opus 5.5, Claude Sonnet 5.5, GPT-6 Astra and GPT-6 Sol, to optimize performance, cost and latency per task. In Artificial Analysis' Coding Agent Index v2.0, its max setting in GitHub Copilot CLI scored 2 points below Opus 5.5 in Claude Code at half the cost per task ($5.59 versus $11.42), leading Terminal-Bench 4.0 at 71 while ranking third on FrontierCode at 51 and scoring 57 on SWE-Atlas-QnA-AA. It used 7.2M tokens per task, roughly half of Claude Opus 5.5 in Claude Code and 30% less than Devin Fusion with Opus 5.5 (max) + GPT-6 Luna (high).
Why it matters: Offers concrete benchmark and cost comparisons for a multi-model orchestration approach, useful for readers weighing coding-agent performance against token spend.