AI 评测与排行榜,分别告诉你什么
分清评测基准、一次评测运行与排行榜,用它们回答各自适合的问题。
LLM Stats
AlpacaEval 2.0 is a length-controlled automatic evaluator for instruction-following language models that uses GPT-4 Turbo to assess model responses against a baseline. It evaluates models on 805 diverse instruction-following tasks including creative writing, classification, programming, and general knowledge questions. The benchmark achieves 0.98 Spearman correlation with ChatBot Arena while being fast (< 3 minutes) and affordable (< $10 in OpenAI credits). It addresses length bias in automatic evaluation through length-controlled win-rates and uses weighted scoring based on response quality.
本站保留来源报告的结果,不代表独立复测。请先核对任务版本、评测协议、分数单位和报告日期;不同运行条件不能直接合并为统一排名。
按来源中的观察顺序展示,顺序不代表排名。日期保留原始精度。
| 模型 | 数值 | 单位 | 协议 | 报告日期与口径 | 来源 |
|---|---|---|---|---|---|
| Granite 3.3 8B Base | 0.6268 | 未收录 | 未收录 | 2025-04-16 · model_announcement | LLM Stats |
| Granite 3.3 8B Instruct | 0.6268 | 未收录 | 未收录 | 2025-04-16 · model_announcement | LLM Stats |
| DeepSeek-V2.5 | 0.505 | 未收录 | 未收录 | 2024-05-08 · model_announcement | LLM Stats |
| IBM Granite 4.0 Tiny Preview | 0.3516 | 未收录 | 未收录 | 2025-05-02 · model_announcement | LLM Stats |