Measuring Short-Form Factuality in Large Language Models

A benchmark that evaluates the ability of language models to answer short, fact-seeking questions accurately. Focuses on factual correctness rather than reasoning complexity.

ModelsModels with a result.14
Top resultBest result on this benchmark.62.5%GPT-4.5
Top-3 spreadPoints from first to third.18.9 pts
YearYear of release.2024

Result and price

9 of 14 results

Results

14 results
#ModelResultThe score from the source.
01GPT-4.5Above fitFar above this model's index.62.5%
04Kimi K231.0%
09o4-mini20.2%
14o1-mini7.6%