稀宇科技技术报告揭示，M2系列模型无法准确输出“马嘉祺”等特定人名，根源在于分词器导致的“词元偏移”问题。模型将名字切分为“马”和“嘉祺”，使得向量空间被挤压，造成识别偏差。这暴露了当前大模型训练中一个普遍但隐蔽的缺陷，影响了特定人名的精确生成。
MiniMax M2系列模型在输出“马嘉祺”时出现异常，原因是后训练阶段导致低频Token退化。排查发现，分词器将“马嘉祺”切分为[马，嘉祺]，“嘉祺”因预训练高频被合并为独立Token（编号190467），但在后续训练中该Token被“挤压”，引发输出错误。官方已发布技术报告，揭示了这一机制。
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