AI Agent Teams Underperform
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AI agent teams, including GPT-6 Sol and Claude Opus 5.5, tested by Vals AI, yielded almost no better results than single agents. The teams cost up to 5.1 times more than single agents, with only one instance showing a statistically significant improvement. At maximum reasoning, the team setup did not provide any real advantage, suggesting the additional cost is not justified in most cases. Vals AI conducted the tests on the 'Vibe Code Bench', revealing that the teams' extra cost is not worth the marginal quality gains, especially when models are already operating at full compute. The findings challenge the conventional wisdom about the benefits of AI agent teams, highlighting the inefficiency of such approaches.
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- The Decoder研究发现：AI智能体团队浪费大量token以换取微小的质量提升
研究发现，AI智能体团队在大多数情况下几乎无法比单个智能体提供更好的结果。在Vals AI的基准测试中，GPT-6 Sol和Claude Opus 5.5作为团队在中等和最大推理努力水平上测试时，团队的成本比单个智能体高出1.8倍到5.1倍。只有一次比较显示团队有统计学上显著的改进，但在最大推理努力水平下，团队设置并没有给Sol或Opus 5.5带来任何实际优势。
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还没有足够的连续观测数据，暂不绘制趋势。