Event ·Multi-source

AA-PersonalityBench 统计:GLM-5.3 平均每条回复用 7.4 个破折号居首

Artificial Analysis 在 AA-PersonalityBench 中统计了各模型回复中破折号(em dash)的使用频率。GLM-5.3 平均每条回复使用 7.4 个破折号,GLM-5.3-Flash 为 6.9 个,Kimi K3 为 6.7 个。Claude 系列几乎不用:Opus 5.5 平均每 40 条回复不到 1 个(0.02),Sonnet 5.5 与 Haiku 5.5 为 0.00。Claude Fable 5.1 平均 6.4 个,是 Claude 系列中的例外。GPT-3.5 Turbo 为 0.00。

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Artificial Analysis 数了各模型写破折号的频率,GLM-5.3 一条回复平均 7.4 个,Claude Opus 5.5 几乎为零,看你的模型像谁就靠这个。

6 sources33° AI heatLast updated 2026/11/4 17:00:00

Evidence

6 sources
Primary sourceArtificial Analysis
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Related source 1Thomas Wolf
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Related source 2AWS Machine Learning Blog
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Related source 3lmarena.ai
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Related source 4marktechpost
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Conflict check

Dedup data only shows that these sources discuss the same event, not that they agree. There is no structured supporting or refuting evidence yet, so no conflict is inferred automatically.