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Devin Fusion matches top coding agents at lower cost per task

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From the Daily Brief

Artificial Analysis benchmarked Cognition's Devin Fusion CLI with Claude Opus 5.5 at max effort as the lead and GPT-6 Luna on high as a sidekick. The two run in parallel with their own context and tools, while the lead keeps planning, delegation and final review. Fusion scored 68.1 on the Coding Agent Index, close to Claude Code with Sonnet 5.5 at 68.4 and Muse Code with Muse Wonder Full at 68.0. Against Claude Code running the same Opus 5.5 lead, which scored 66.0, Fusion cost $9.01 per task instead of $13.04 and took 55 minutes on average instead of 65. The gains are uneven across the index: Fusion leads on DeepSWE v1.1 at 72.6% against 68.4% and on SWE-Atlas-QnA at 69.6% against 66.4%, but trails slightly on Terminal-Bench 4.0, 62.1% against 63.1%. The figures include both models' API costs at pay-per-token rates, not subscription prices, so the saving shows up for teams billed by the token.

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Artificial Analysis@ArtificialAnlys

Devin Fusion with Claude Opus 5.5 (max) and a GPT-6 Luna (high) sidekick scores 68 on the Coding Agent Index, 2 points above Claude Code with Opus 5.5 (max) at 31% lower cost per task @cognition's Devin Fusion runs a frontier lead model alongside a lower-cost sidekick model. The two work in parallel with their own context and tools, with the lead keeping planning, delegation and final review. We benchmarked Devin Fusion CLI with Claude Opus 5.5 (max) + GPT-6 Luna (high). It scores 68.1 on the Artificial Analysis Coding Agent Index, closely matched at the top with Claude Code with Claude Sonnet 5.5 (max) at 68.4 and Muse Code with Muse Wonder Full (max) at 68.0. Against Claude Code with Claude Opus 5.5 (max) at 66.0, it costs $9.01 vs. $13.04 per task and averages 55 vs. 65 minutes per task. Across the three benchmarks, the Fusion configuration scores higher on DeepSWE v1.1 (72.6% vs. 68.4%) and SWE-Atlas-QnA (69.6% vs. 66.4%) and slightly lower on Terminal-Bench 4.0 (62.1% vs. 63.1%). Its results reflect both models working together, including their combined API cost. Costs are pay-per-token API costs, not subscription prices.

Context

Artificial Analysis, which runs its own benchmarks of coding agents, tested Cognition's Devin Fusion command-line configured with Claude Opus 5.5 at max effort as the lead model and GPT-6 Luna at high effort as a cheaper 'sidekick'. It scored 68.1 on the firm's Coding Agent Index. Claude Code running Opus 5.5 by itself scored 66.0. According to Artificial Analysis, the Fusion run cost $9.01 per task against $13.04 and averaged 55 minutes per task against 65. That puts it in a near tie at the top with Claude Code using Sonnet 5.5 at 68.4 and Muse Code using Muse Wonder Full at 68.0.

The setup splits one coding job across two models from different labs, Anthropic for the lead and OpenAI for the sidekick. As Artificial Analysis describes it, the two run in parallel, each with its own and tools, and the lead keeps planning, delegation and final review. The reported score and cost cover both models working together, including their combined API bill. The post does not say how much of the work the sidekick handled. The comparison also changes the agent software itself, Cognition's tool versus Claude Code, so the result shows what this whole configuration achieved, not how much of the saving comes from the second model.

The index is a simple average of three benchmarks, and each score is the average pass rate over three attempts per task, according to the Coding Agent Index page. DeepSWE v1.1 covers software engineering tasks, Terminal-Bench 4.0 covers multi-step work in a shell, and SWE-Atlas-QnA covers technical questions about a codebase. Fusion beat solo Opus 5.5 on DeepSWE, 72.6% to 68.4%, and on SWE-Atlas-QnA, 69.6% to 66.4%. It came in slightly lower on Terminal-Bench, 62.1% to 63.1%. Costs are pay-per- API prices, and the page notes that many people use these tools through subscription plans instead, so the dollar gap shows relative token spend, not what a subscriber pays.

This is not Artificial Analysis's first Devin Fusion run. In September it benchmarked the launch configurations, which paired a frontier lead with Cognition's own SWE-2 model as the sidekick and scored 62 with Claude Fable 5.1 as the lead. The $13.04 comparison figure comes from the firm's earlier Opus 5.5 test, which found that Opus 5.5 topped the index at the time but used substantially more tokens per task than its predecessor. In the new run, Opus 5.5 working inside Fusion with a cheaper sidekick came out slightly ahead on score and well below on cost.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
  • benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
  • token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
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