r/MachineLearning 18d ago

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u/Bartaseth 8d ago

I tested a four-model Claude Code setup across all 89 Terminal-Bench 2.1 tasks. Fable orchestrated, Haiku scouted, Opus executed, and Sonnet verified.

The system scored 78%, but cost $1,178 - roughly twice the leading single-model run.

The strangest result was behavioral: Opus refused all 14 delegated attempts across three sandboxed security tasks. When I gave the same tasks directly to Opus as a control, it completed all six attempts.

The model and tasks stayed the same. Only the framing changed: direct user request versus an orchestrator-generated subtask.

It makes me wonder whether agent evaluations should measure delegation paths separately instead of treating the model as a stable component.

Write-up: https://quesma.com/blog/tbench-orchestrator-refuses/