UC Berkeley 等发布 Route Anything 研究：模型路由平均提升 8.82 倍成本效率
UC Berkeley 等机构发布 Route Anything 研究，在 25 个基准、452 个候选模型与策略、374,401 次评分运行上系统评估模型路由，发现路由平均带来 8.82 倍单位成本质量效率提升，质量损失不到 0.5 分。
Rohan Paul· @rohanpaul_ai · X·2026-11-11 01:37· 2 小时前AI 评分58
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UC Berkeley 等机构的 Route Anything 研究系统评估模型与策略路由，发现在 25 个基准上，路由平均带来 8.82 倍的单位成本效率提升，质量损失不到 0.5 分。
正文 · 原文
Great new study on model routing.
From University of California, Berkeley + other labs
Finds that model routers pay off significantly by saving money, averaging 8.82X more quality per unit cost while losing under 0.5 points.
Routers pick which model handles each input, hoping to match the best model for less or beat it. Most routing research has studied only language models.
Route Anything ran 452 candidate models and policies on the same inputs across 25 benchmarks, from text QA to robot control. They trained routers on these 374,401 scored runs and measured both quality and cost.
A perfect per-input router would beat the best single model by 5.4 points, but learned routers gained only 0.3 across 16 benchmarks. On coding tasks, routing reached 25.5× the dollar efficiency of always calling Opus 4.6 at a 0.44-point loss.
Use routers mainly to move work to cheaper models when quality is close, and compare candidates on the same inputs before trusting gains.
来源：Rohan Paul · x.com
来源：RadarAI · aihot.news