Benchmark
Scale MultiChallenge
reasoning
communication
general
text
MultiChallenge is a realistic multi-turn conversation evaluation benchmark developed by Scale AI that evaluates large language models on four challenging conversation categories: instruction retention, inference memory of user information, reliable versioned editing, and self-coherence. Each challenge requires accurate instruction-following, context allocation, and in-context reasoning. Despite achieving near-perfect scores on existing multi-turn evaluation benchmarks, all frontier models have less than 50% accuracy on MultiChallenge.
Top 10
榜单概览
数据说明
分数为 0-100 百分制综合成绩(Elo 榜为相对评分,仅供同榜内比较)。评测分数属事实数据,整理自公开评测体系与厂商公开资料,部分分数为厂商自报口径,不同榜单的评测方法与数据集可能存在差异,请结合多个榜单交叉参考。
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