SyntheticIntermediateFemaleCheck detectors from our latest benchmark
Pick a detector and a condition and see how it scores on our corpus, down to a single demographic cell. The same measurement we run in an evaluation. Full results are on our benchmark page.
Query the benchmark
AUC is a 0 to 1 score for how well a detector tells fake images from real ones. Picture showing it one fake photo and one real photo: AUC is how often it rates the fake as the more likely fake. 1.0 means it always gets it right, 0.5 is a coin flip (no better than guessing), and below 0.5 means it is getting them backwards.
Put in a request
Public model
We'll run it and put it up on the interactive.
Private model
Share it privately. Weights or API Key.
Request a generator
Suggest one to add to the interactive.
Want the full report on your detector?
The interactive shows one score at a time. A full evaluation runs your model across the entire sequestered corpus and returns a per-group report card: AUC with DeLong confidence intervals, how it holds up under each platform condition, and where it fails, the recipe that broke it.