StudioGoogle Research tested 180 agent configurations: multi-agent setups degraded a sequential task by 39 to 70% and improved a parallel one by 80.9%
A Google Research study ran a controlled evaluation of 180 agent configurations, comparing a single agent with several multi-agent designs across benchmarks. Every multi-agent variant degraded performance by 39 to 70% on the sequential planning task PlanCraft, while multi-agent setups improved performance by 80.9% on the parallelizable financial reasoning task Finance-Agent. The author adds their own interpretation: more agents may be worth it when task pieces run independently, but handoffs can fragment reasoning when each step depends on the previous one, so a single agent is worth testing first. They note these are benchmark results, not a rule for every real workflow.
The study offers controlled evidence across 180 agent configurations that task structure determines whether multi-agent setups help, useful for deciding whether to split a workflow.
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