RMGAP - EndoRM - Best-of-4: leaderboard
RMGAP (Zhou and Li, 2026) tests whether reward models follow a preference stated in the prompt: each of 1,097 instances pairs four responses in deliberately different styles with prompts that each ask for one of those styles (three paraphrases each), across chat, writing, reasoning and safety. The reward is the model's discounted sum of token log-probabilities of the response (EndoRM). Best-of-4 accuracy is the percentage of cases in which the requested response scores above all three alternatives, averaged over the four domains; higher is better.
Metric: Best-of-4 accuracy (%; chosen response scored above all three alternatives, mean of chat, writing, reasoning and safety; discounted sum of the model's token log-probabilities of the response (gamma 0.93)). Source: arxiv.org. Saturation forecast: Around February 2027. 2 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen 2.5 7B Instruct | 37.16 | #2583 |
| 2 | Qwen 3 8B | 36.1 | #1838 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=rmgap-endorm-best-of-4 · How It Works · Data refreshed daily, snapshot 2026-11-12.