Performance–cost parity of task decomposition versus frontier reasoning models

Determine whether multi‑agent task decomposition can systematically match frontier reasoning model performance while achieving substantially reduced computational and environmental costs.

Background

Mimosa attains ScienceAgentBench success rates comparable to those reported with very costly frontier reasoning models, suggesting a pathway to frugal scientific AI. However, the generality of this observation is not established. Establishing whether decomposition can consistently reach similar performance at lower cost would guide practical deployment and model–architecture choices.