Sci-Rho - Worst-Case: leaderboard

Sci-Rho (Science Rhobustness, 2026) is a dynamic benchmark of image-grounded STEM problems in five subjects and seven languages, where each expert-written template generates ten visually and numerically varied instances. This board is worst-case accuracy (%), the share of templates answered correctly on every generated variant, averaged over the seven languages; higher is better.

Metric: Worst-case accuracy (%) over all seven languages on 606 expert-written executable templates per language (mathematics, physics, chemistry, biology and computer science, many drawn from olympiad problems), each rendered as 10 visually and numerically varied image-grounded instances: the share of templates a model answers correctly on every one of its 10 generated variants, averaged over languages; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 17 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.4 (Non-reasoning)73.9#123 (GPT-5.4)
2Gemini 2.5 Pro62.5#266
3Gemini 2.5 Flash (Non-reasoning)56.6#453 (Gemini 2.5 Flash)
4Qwen 3.5 27B (Non-reasoning)51.2#359 (Qwen 3.5 27B)
5Qwen 3.5 122B A10B (Non-reasoning)43.6#331 (Qwen 3.5 122B A10B)
6Llama 4 Scout Instruct33.7#1543
7Qwen 3 VL 8B Instruct29.5#981
8Gemma 3 12B (IT)18.7#1837
9Molmo2-8B15.5#1483
10Gemma 3 4B (IT)7.2#3831
11Qwen 3 VL 4B Instruct3.3#1279

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

Interactive version: theaggregate.ai/benchmark?slug=sci-rho-worst-case · How It Works · Data refreshed daily, snapshot 2026-11-13.