Abstract
Each model is assigned a position on two unlabeled axes by a uniform random draw. The benchmark is re-run on every deploy of this site, and on demand in your browser. In internal testing it has shown predictive validity comparable to several launch-day charts.
Results
Random Axis · pts · Direction unclear · re-randomized every deploy
Methodology
- Seed: the build timestamp. Distribution: Uniform(0, 100) on both axes.
- Axes are left unlabeled, in keeping with industry practice.
- Results change every run. So do most leaderboards; this one is simply upfront about it.
Limitations
- None identified. It is the only benchmark on this site that makes no claim it cannot support.
Citation
@misc{tmb2026randomaxis,
title = {Random X/Y Axis Placement: AI models randomly sorted on an X and Y axis},
author = {Bro, Trust Me and {et al.}},
year = {2026},
howpublished = {\url{https://trustmebrobenchmarks.com/benchmarks/random-axis/}},
note = {Results not reproducible. Please do not cite.}
}