Artificial Analysis Intelligence Index v5.0 combines 9 evaluation datasets to assess language model capabilities across reasoning, knowledge, math, and programming. It evaluates models using a weighted average across four categories: Knowledge Work (25%), Coding (25%), Science (25%), and General (25%).
The suite includes evaluations like AA-Briefcase v1.1, Automation Bench-AA, GDP.pdf, Frontier Code 2.0, Terminal-Bench 4.0, AA-Omniscience v1.1, HLE-Diamond, Crit Pt v2, and Terminal-Bench-Science 0.1.0. Each evaluation uses different metrics like Elo ratings, pass/fail scoring, and rubric-based grading.
The methodology emphasizes fairness and real-world applicability, focusing on text-based, English-language evaluation. Separate benchmarks exist for image, speech, and multilingual performance.
Source: Hacker News · Summarized by HeadlinesBriefing