RPCBench - Domain - Yelp Local - Composite Premise Critique: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures composite premise critique on the Yelp Local subset (1,310 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
1Qwen 3.5 122B A10B60.95#335
2DeepSeek V4 Pro60.08#188
3Qwen 3.5 Plus59.82#232
4Qwen 3.5 397B A17B59.26#245
5GPT-5.558.62#48
6Gemini 3.1 Pro (Preview)57.68#93
7Qwen 3.5 35B A3B57.38#492
8Claude Sonnet 4.656.66#159
9DeepSeek V4 Flash55.42#259
10Llama 3.1 70B Instruct16.71#1629
11Llama 3.1 8B Instruct10.39#4318

No result here: #4 Claude Opus 5.5, #5 GPT-6 Astra, #9 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=rpcbench-domain-yelp-local-composite-premise-critique · How It Works · Data refreshed daily, snapshot 2026-11-08.