RPCBench - Domain - MIND-small - Composite Premise Critique: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures composite premise critique on the MIND-small subset (703 questions), using the same eleven-model, three-judge experiment as the headline paper. Published CPCC fractions from the authors' per-model CSV are scaled once to Composite Score (0-100). Higher is better; domains and nested premise-error groups are related slices of the same experiment.

Metric: Composite Score (0-100). Source: github.com. Saturation forecast: Around May 2027. 11 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.641.96#97
2DeepSeek V4 Pro41.49#113
3GPT-5.539.66#34
4Qwen 3.5 122B A10B39.01#186
5Qwen 3.5 Plus38.59#136
6Qwen 3.5 397B A17B38.24#155
7Gemini 3.1 Pro (Preview)38.07#66
8DeepSeek V4 Flash36.19#156
9Qwen 3.5 35B A3B35.13#270
10Llama 3.1 70B Instruct9.21#570
11Llama 3.1 8B Instruct6.33#1021

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #6 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=rpcbench-domain-mind-small-composite-premise-critique · How It Works · Data refreshed daily, snapshot 2026-11-07.