[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"model-image-service-v2-claude-fable-5":3,"text-service-v2-claude-fable-5@lite":296},[4,196],{"id":5,"aliases":6,"types":8,"pricing_group":11,"pricing":12,"display_name":5,"tier":18,"model_capabilities":19,"model_capabilities_zh":93,"introduction":142,"introduction_zh":143,"description":144,"description_zh":145,"title_focus":146,"title_focus_zh":147,"keyword_extras":148,"keyword_extras_zh":151,"model_data":154},"claude-fable-5",[7],"claude-fable-5@lite",[9,10],"openai","anthropic","anthropic\u002Fclaude-lite",{"flat_tokens":13},{"input_tokens":14,"output_tokens":15,"cache_read_tokens":16,"cache_write_tokens":17},"5","25","0.5","6.25","lite",{"groups":20,"highlights":81,"overall":85,"scenario":88,"summary":91,"weakness":92},[21,59,72],{"items":22,"name":58},[23,29,34,38,42,46,49,53],{"detail":24,"method":25,"name":26,"samples":27,"score":28},"","Mixed","Agent Collaboration",18,78,{"detail":24,"method":30,"name":31,"samples":32,"score":33},"Objective","Code Generation",12,67,{"detail":24,"method":25,"name":35,"samples":36,"score":37},"Code Comprehension & Debugging",6,87,{"detail":24,"method":25,"name":39,"samples":40,"score":41},"Creative Writing",22,79,{"detail":24,"method":25,"name":43,"samples":44,"score":45},"Information Retrieval \u002F RAG",9,77,{"detail":24,"method":25,"name":47,"samples":48,"score":37},"Long-Context Handling",16,{"detail":24,"method":25,"name":50,"samples":51,"score":52},"Math & Science Reasoning",14,85,{"detail":24,"method":54,"name":55,"samples":56,"score":57},"Subjective","Multilingual Capability",11,88,"Advanced Capabilities",{"items":60,"name":71},[61,65,68],{"detail":24,"method":25,"name":62,"samples":63,"score":64},"General Knowledge",10,91,{"detail":24,"method":54,"name":66,"samples":67,"score":52},"Text Comprehension",23,{"detail":24,"method":25,"name":69,"samples":48,"score":70},"Logical Reasoning",72,"General Foundations",{"items":73,"name":80},[74,77],{"detail":24,"method":25,"name":75,"samples":76,"score":64},"Hallucination Control",15,{"detail":24,"method":54,"name":78,"samples":27,"score":79},"Instruction Following",83,"Safety & Compliance",[82,83,84],{"name":62,"score":64},{"name":75,"score":64},{"name":55,"score":57},{"rating":86,"score":87},"良好",82,{"fit":89,"name":90},86,"Translation & Localization \u002F Customer Support \u002F E-commerce Copywriting","Claude Fable 5 scored 82 overall, performing well — a language and content specialist. It stands out in general knowledge (91%), hallucination control (91%) and multilingual capability (88%), writing fluently across languages with few fabrications, which makes it strong for localization, support replies and marketing copy. Comparatively, code generation (67%) is moderate; coding is not its focus. Language- and content-heavy work is where it clearly wins.",{"name":31,"note":24,"score":33},{"groups":94,"highlights":133,"overall":137,"scenario":138,"summary":140,"weakness":141},[95,117,126],{"items":96,"name":116},[97,100,103,105,107,109,111,113],{"detail":24,"method":98,"name":99,"samples":27,"score":28},"主\u002F客观混合","智能体协同",{"detail":24,"method":101,"name":102,"samples":32,"score":33},"客观","代码生成",{"detail":24,"method":98,"name":104,"samples":36,"score":37},"代码理解与调试",{"detail":24,"method":98,"name":106,"samples":40,"score":41},"创意写作",{"detail":24,"method":98,"name":108,"samples":44,"score":45},"信息检索 \u002F RAG",{"detail":24,"method":98,"name":110,"samples":48,"score":37},"长文本处理",{"detail":24,"method":98,"name":112,"samples":51,"score":52},"数学与科学推理",{"detail":24,"method":114,"name":115,"samples":56,"score":57},"主观","多语言能力","专项进阶能力",{"items":118,"name":125},[119,121,123],{"detail":24,"method":98,"name":120,"samples":63,"score":64},"通识知识",{"detail":24,"method":114,"name":122,"samples":67,"score":52},"文本理解",{"detail":24,"method":98,"name":124,"samples":48,"score":70},"逻辑推理","通用基础能力",{"items":127,"name":132},[128,130],{"detail":24,"method":98,"name":129,"samples":76,"score":64},"幻觉控制",{"detail":24,"method":114,"name":131,"samples":27,"score":79},"指令遵循","安全与合规能力",[134,135,136],{"name":120,"score":64},{"name":129,"score":64},{"name":115,"score":57},{"rating":86,"score":87},{"fit":89,"name":139},"翻译与本地化 \u002F 智能客服 \u002F 电商营销文案","Claude Fable 5 综合得分 82，整体表现良好，是一款语言与内容专精模型。通识知识（91%）、幻觉控制（91%）与多语言能力（88%）表现突出，跨语言行文流畅且极少虚构，在翻译本地化与电商营销文案场景中优势明显。相对而言，代码生成（67%）一般，编码不是它的重心。语言与内容密集型工作选它优势明显。",{"name":102,"note":24,"score":33},"Claude Fable 5 is Anthropic's new model for language and content tasks, with standout multilingual capability and factual accuracy — suited to translation, customer support and e-commerce copywriting.","Claude Fable 5是Anthropic面向内容与语言任务的新模型，多语言能力和事实准确性表现突出，适合翻译与本地化、智能客服和电商营销文案创作。","Claude Fable 5 strengthens multilingual understanding, hallucination control and text creation for high-quality translation, support Q&A and content production. Integrate in one click via the SilvaMux unified API.","Claude Fable 5强化多语言理解、幻觉控制与文本创作，适合高质量翻译、客服问答与内容生产。可通过 SilvaMux 统一 API 一键快速接入。","Multilingual Content Model","多语言内容模型",[149,150],"translation & localization","content creation",[152,153],"翻译本地化","内容创作",{"summary":155,"recentAvailability":168,"observedAt":24,"bars":169,"metrics":174},[156,160,164],{"label":157,"value":158,"unit":159},"modelsDetail.performance.latency","25.70","s",{"label":161,"value":162,"unit":163},"modelsDetail.performance.throughput","82.47K","tokens\u002Fmin",{"label":165,"value":166,"unit":167},"modelsDetail.performance.availability","99.8","%","99.8%",{"degraded":170,"down":171},[],[172,173],4,48,[175,178,181,185,189,192],{"label":176,"value":177},"modelsDetail.performance.completionRate","97%",{"label":179,"value":180},"modelsDetail.performance.cacheHitRate","98%",{"label":182,"value":183,"unit":184},"modelsDetail.performance.tokenUsage","2,790,427,472","tokens",{"label":186,"value":187,"unit":188},"modelsDetail.performance.avgRequests","43","modelsDetail.performance.requestsUnit",{"label":190,"value":191,"unit":163},"modelsDetail.performance.tpm","82,467",{"label":193,"value":194,"unit":195},"modelsDetail.performance.qpm","842","req\u002Fmin",{"id":5,"aliases":197,"types":198,"pricing_group":199,"pricing":200,"display_name":5,"capabilities":206,"model_capabilities":211,"model_capabilities_zh":239,"introduction":142,"introduction_zh":143,"description":144,"description_zh":145,"title_focus":146,"title_focus_zh":147,"keyword_extras":267,"keyword_extras_zh":268,"model_data":269},[5],[9,10],"anthropic\u002Fclaude",{"flat_tokens":201},{"input_tokens":202,"output_tokens":203,"cache_read_tokens":204,"cache_write_tokens":205},"10","50","1","12.5",{"context_window":207,"max_output":208,"modalities":209},1048576,131072,[210],"text",{"groups":212,"highlights":232,"overall":236,"scenario":237,"summary":91,"weakness":238},[213,223,228],{"items":214,"name":58},[215,216,217,218,219,220,221,222],{"detail":24,"method":25,"name":26,"samples":27,"score":28},{"detail":24,"method":30,"name":31,"samples":32,"score":33},{"detail":24,"method":25,"name":35,"samples":36,"score":37},{"detail":24,"method":25,"name":39,"samples":40,"score":41},{"detail":24,"method":25,"name":43,"samples":44,"score":45},{"detail":24,"method":25,"name":47,"samples":48,"score":37},{"detail":24,"method":25,"name":50,"samples":51,"score":52},{"detail":24,"method":54,"name":55,"samples":56,"score":57},{"items":224,"name":71},[225,226,227],{"detail":24,"method":25,"name":62,"samples":63,"score":64},{"detail":24,"method":54,"name":66,"samples":67,"score":52},{"detail":24,"method":25,"name":69,"samples":48,"score":70},{"items":229,"name":80},[230,231],{"detail":24,"method":25,"name":75,"samples":76,"score":64},{"detail":24,"method":54,"name":78,"samples":27,"score":79},[233,234,235],{"name":62,"score":64},{"name":75,"score":64},{"name":55,"score":57},{"rating":86,"score":87},{"fit":89,"name":90},{"name":31,"note":24,"score":33},{"groups":240,"highlights":260,"overall":264,"scenario":265,"summary":140,"weakness":266},[241,251,256],{"items":242,"name":116},[243,244,245,246,247,248,249,250],{"detail":24,"method":98,"name":99,"samples":27,"score":28},{"detail":24,"method":101,"name":102,"samples":32,"score":33},{"detail":24,"method":98,"name":104,"samples":36,"score":37},{"detail":24,"method":98,"name":106,"samples":40,"score":41},{"detail":24,"method":98,"name":108,"samples":44,"score":45},{"detail":24,"method":98,"name":110,"samples":48,"score":37},{"detail":24,"method":98,"name":112,"samples":51,"score":52},{"detail":24,"method":114,"name":115,"samples":56,"score":57},{"items":252,"name":125},[253,254,255],{"detail":24,"method":98,"name":120,"samples":63,"score":64},{"detail":24,"method":114,"name":122,"samples":67,"score":52},{"detail":24,"method":98,"name":124,"samples":48,"score":70},{"items":257,"name":132},[258,259],{"detail":24,"method":98,"name":129,"samples":76,"score":64},{"detail":24,"method":114,"name":131,"samples":27,"score":79},[261,262,263],{"name":120,"score":64},{"name":129,"score":64},{"name":115,"score":57},{"rating":86,"score":87},{"fit":89,"name":139},{"name":102,"note":24,"score":33},[149,150],[152,153],{"summary":270,"recentAvailability":277,"observedAt":24,"bars":278,"metrics":284},[271,273,275],{"label":157,"value":272,"unit":159},"53.42",{"label":161,"value":274,"unit":163},"82.36K",{"label":165,"value":276,"unit":167},"99.6","99.6%",{"degraded":279,"down":281},[280],0,[282,283],43,50,[285,287,289,291,292,294],{"label":176,"value":286},"95%",{"label":179,"value":288},"99%",{"label":182,"value":290,"unit":184},"2,453,087,655",{"label":186,"value":187,"unit":188},{"label":190,"value":293,"unit":163},"82,360",{"label":193,"value":295,"unit":195},"993",{"ttft":297,"tps":300,"e2e":303,"requests":306,"successfulRequests":307,"successRate":308,"availability":309},{"p50":298,"p95":299},2428,2452,{"p50":301,"p95":302},31,100,{"p50":304,"p95":305},3470,4216,63622,62962,"98.96",[310,310,310,310,310,311,310,310,310,310,310,310,310,310,310,310,310,310,310,310,310,310,310,310],"up","degraded"]