[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"model-minimax-m2.5":3},[4,143],{"id":5,"aliases":6,"types":7,"pricing":11,"capabilities":17,"model_capabilities":23,"model_data":98},"minimax-m2.5",[5],[8,9,10],"openai","anthropic","openai\u002Fresponses\u002Fv1",{"flat_tokens":12},{"input_tokens":13,"output_tokens":14,"cache_read_tokens":15,"cache_write_tokens":16},"2.1","8.4","0.21","2.625",{"context_window":18,"max_output":19,"released_at":20,"modalities":21},204800,196608,"2026-02-12",[22],"text",{"groups":24,"highlights":87,"overall":91,"scenario":94,"summary":96,"weakness":97},[25,63,77],{"items":26,"name":62},[27,33,38,43,47,51,55,59],{"detail":28,"method":29,"name":30,"samples":31,"score":32},"","主\u002F客观混合","智能体协同",7,36,{"detail":28,"method":34,"name":35,"samples":36,"score":37},"客观","代码生成",10,0,{"detail":28,"method":39,"name":40,"samples":41,"score":42},"主观","代码理解与调试",12,68,{"detail":28,"method":39,"name":44,"samples":45,"score":46},"创意写作",17,77,{"detail":28,"method":29,"name":48,"samples":49,"score":50},"信息检索 \u002F RAG",13,55,{"detail":28,"method":39,"name":52,"samples":53,"score":54},"长文本处理",3,50,{"detail":28,"method":34,"name":56,"samples":57,"score":58},"数学与科学推理",14,93,{"detail":28,"method":29,"name":60,"samples":36,"score":61},"多语言能力",64,"专项进阶能力",{"items":64,"name":76},[65,68,72],{"detail":28,"method":29,"name":66,"samples":67,"score":50},"通识知识",15,{"detail":28,"method":39,"name":69,"samples":70,"score":71},"文本理解",5,76,{"detail":28,"method":29,"name":73,"samples":74,"score":75},"逻辑推理",20,72,"通用基础能力",{"items":78,"name":86},[79,83],{"detail":28,"method":39,"name":80,"samples":81,"score":82},"幻觉控制",9,83,{"detail":28,"method":39,"name":84,"samples":57,"score":85},"指令遵循",78,"安全与合规能力",[88,89,90],{"name":56,"score":58},{"name":80,"score":82},{"name":84,"score":85},{"rating":92,"score":93},"良好",62,{"fit":93,"name":95},"高准确率专业场景 \u002F 数学与科学计算","综合能力 62 分（良好）。优势集中在 数学与科学推理（93%）、幻觉控制（83%）、指令遵循（78%）。相对短板为 代码生成（0%）。适合 高准确率专业场景 \u002F 数学与科学计算 等场景。在 代码生成 类任务上建议结合人工复核或专项验证。",{"name":35,"note":28,"score":37},{"bars":99,"metrics":104,"recentAvailability":131,"summary":132},{"degraded":100,"down":101},[],[37,102,103,53],1,2,[105,108,111,115,119,123,127],{"label":106,"value":107},"完成率","98%",{"label":109,"value":110},"缓存命中率","0.0%",{"label":112,"unit":113,"value":114},"累计评测耗时","s","9439.7",{"label":116,"unit":117,"value":118},"Token 消耗","tokens","418,366",{"label":120,"unit":121,"value":122},"平均请求次数","次","1.0",{"label":124,"unit":125,"value":126},"TPM","tokens\u002Fmin","2,659",{"label":128,"unit":129,"value":130},"QPM","req\u002Fmin","0.9","97.99%",[133,136,139],{"label":134,"unit":113,"value":135},"延迟","22.71",{"label":137,"unit":125,"value":138},"吞吐量","2.66K",{"label":140,"unit":141,"value":142},"可用率","%","97.99",{"id":5,"aliases":144,"types":146,"pricing":147,"capabilities":150,"tier":152,"priority":102},[145,5],"aliyun\u002FMiniMax-M2.5",[8],{"flat_tokens":148},{"input_tokens":13,"output_tokens":14,"cache_read_tokens":149,"cache_write_tokens":13},"0.42",{"context_window":18,"max_output":19,"released_at":20,"modalities":151},[22],"tune"]