RubricBench: leaderboard

Metric: Preference accuracy (%) on RubricBench's 1,147 preference pairs (instruction following, STEM, code, safety and chat pairs re-curated from HelpSteer3, PPE and RewardBench2 and filtered so that surface cues such as length, formatting or tone favour the rejected response); the reward model or LLM judge picks the preferred response directly, with no rubric; higher is better. Source: arxiv.org. Saturation forecast: Around 2031. 15 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro57.3#77
2Qwen 3.5 Plus56.9#123
3Gemini 3 Flash56.4#93
4GPT-OSS-120B52#330
5GPT-5.151.5#131
6ArmoRM-Llama3-8B-v0.150.3#1375
7Llama-3.1-Tulu-3-8B-RM47.1#790
8GPT-4o Mini40.2#588
9DeepSeek V3.2 (Non-reasoning)38.8#198 (DeepSeek V3.2)

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=rubricbench · How It Works · Data refreshed daily, snapshot 2026-10-11.