主流 AI 模型编程推理 effort 与成本效益评测发布
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2026年11月5日，CodingPlans 针对主流 AI 模型在编程场景下的表现发布了评测与选择指南。该评测基于 FrontierCode 2.0 基准展开，系统测算了各大主流模型在从 low 到 max 等各个 effort 档位下的具体表现，涵盖了相应的基准得分、单任务成本以及 token 消耗情况。评测旨在量化分析不同 effort 档位下的性能产出与资源开销，为编程应用场景中合理选择 AI 模型的 effort 档位提供了详细的参考数据。
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- Hacker News · AISelectedA guide to choosing AI model effort levels in coding scenarios
CodingPlans evaluated the coding performance of mainstream models on the FrontierCode 2.0 benchmark, measuring scores, per-task costs, and token consumption across effort levels ranging from 'low' to 'max.'
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