RPCBench - Domain - Amazon Sports - Composite Premise Critique: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures composite premise critique on the Amazon Sports subset (1,270 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 February 2027. 11 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.560.85#34
2Qwen 3.5 397B A17B59.84#155
3Claude Sonnet 4.659.6#97
4Qwen 3.5 Plus59.28#136
5Qwen 3.5 122B A10B56.81#186
6Gemini 3.1 Pro (Preview)55.13#66
7Qwen 3.5 35B A3B53.95#270
8DeepSeek V4 Pro52.3#113
9DeepSeek V4 Flash48.8#156
10Llama 3.1 70B Instruct19.56#570
11Llama 3.1 8B Instruct13.97#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-amazon-sports-composite-premise-critique · How It Works · Data refreshed daily, snapshot 2026-11-07.