所有评测

AA-Omniscience: Knowledge and Hallucination Benchmark

A benchmark measuring factual recall and hallucination across various economically relevant domains.
查看示例任务

AA-Omniscience: Evaluating Cross-Domain Knowledge Reliability in Large Language Models

Declan Jackson、William Keating、George Cameron和Micah Hill-Smith。

AA-Omniscience

Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback)在 AA-Omniscience 中得分最高,为 46;其次是GPT-6 Astra (High),得分 44和Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback),得分 43

AA-Omniscience Accuracy

Claude Fable 5.1 (Adaptive Reasoning, Max Effort, Default Fallback)在 AA-Omniscience Accuracy 中得分最高,为 67%;其次是Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback),得分 66%和Claude Fable 5.1 (Adaptive Reasoning, Xhigh Effort, Default Fallback),得分 66%

AA-Omniscience Hallucination Rate

MiniCPM5-1B (Non-reasoning)在 AA-Omniscience Hallucination Rate 中得分最低,为 1%;其次是G9v3-3B,得分 12%和G9v3-39A5B,得分 13%

得分

AA-Omniscience Index:得分

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.
Not publicly available

AA-Omniscience 指数与每任务成本

AA-Omniscience 指数 · 每任务平均成本(美元)
Most attractive quadrant
Pareto line

AA-Omniscience Index

AA-Omniscience 指数与Artificial Analysis 智能指数

AA-Omniscience 指数 · Artificial Analysis 智能指数
Most attractive quadrant

AA-Omniscience 准确率

AA-Omniscience 准确率

AA-Omniscience Accuracy (higher is better) measures the proportion of correctly answered questions out of all questions, regardless of whether the model chooses to answer
Not publicly available

AA-Omniscience 幻觉率

AA-Omniscience 幻觉率

AA-Omniscience Hallucination Rate (lower is better) measures how often the model answers incorrectly when it should have refused or admitted to not knowing the answer. It is defined as the proportion of incorrect answers out of all non-correct responses, i.e. incorrect / (incorrect + partial answers + not attempted)
Not publicly available

详细领域得分

各领域 AA-Omniscience 指数(标准化)

AA-Omniscience 指数 · 分数按领域在所有测试模型中进行标准化:绿色代表该领域的最高分,红色代表最低分。

软件工程深入分析

各语言软件工程 AA-Omniscience 指数(标准化)

软件工程 AA-Omniscience 指数 · 分数按语言在所有测试模型中进行标准化:绿色代表该语言的最高分,红色代表最低分。

AA-Omniscience 指数题目分布

AA-Omniscience 基准测试中各领域及子领域的问题分布

商业

人文与社会科学

科学、工程与数学

健康

法律

软件工程 (SWE)

模型规模(仅开放权重模型)

AA-Omniscience 指数与总参数量

AA-Omniscience 指数 · 参数规模(十亿)
Most attractive quadrant
Pareto line

AA-Omniscience 准确率与总参数量

AA-Omniscience 准确率 · 参数规模(十亿)
Most attractive quadrant
Pareto line

AA-Omniscience 幻觉率与总参数量

AA-Omniscience 幻觉率 · 参数规模(十亿)
Most attractive quadrant

Token 使用量

AA-Omniscience 指数:Token 用量

评测所用的 Token
Not publicly available

成本

AA-Omniscience:每项任务成本

每项任务的平均成本(美分),按输入、缓存命中、缓存写入、推理和回答 Token 划分
Not publicly available

得分 vs. 发布日期

AA-Omniscience 指数:得分与发布日期

Most attractive region

示例任务

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