PriVE-Bench - Medical Modality: leaderboard

PriVE-Bench (2026) shows vision-language models counterfactual images whose visible content contradicts a familiar prior, such as an unusual part count or logo layout, in five domains, and a text-only judge classifies each answer as correct, prior-consistent or other. This board covers the medical modality domain, which asks about the MRI modality of the tumor region in BraTS 2023 brain scans, a stratified 10 percent subset; score is counterfactual accuracy in percent, higher is better.

Metric: Counterfactual accuracy (%) in the medical modality domain; paired original and counterfactual images in five domains, counterfactual-only input, answers classified by a text-only judge (GPT-4o-mini for closed models, Qwen3-8B for open models); temperature 0, reasoning off or minimal. Source: arxiv.org. Saturation forecast: Around 2031. 8 models tracked.

Top models

#ModelScoreOverall rank
1Gemma 3 12B (IT)66.8#1837
2Claude Sonnet 441.5#400
3Qwen 3 VL 32B Instruct33.1#585
4GPT-5 (Minimal)31.5#167 (GPT-5)
5Qwen 3 VL 8B Instruct27.2#981
6Gemma 3 27B (IT)19.2#1289

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=prive-bench-medical-modality · How It Works · Data refreshed daily, snapshot 2026-11-13.