RPCBench - Domain - Goodreads Dual-Domain - Evidence Distortion: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures evidence distortion on the Goodreads Dual-Domain subset (878 questions), using the same eleven-model, three-judge experiment as the headline paper. Published F1R fractions from the authors' per-model CSV are scaled once to Evidence Distortion Rate (%). Lower is better; domains and nested premise-error groups are related slices of the same experiment.

Metric: Evidence Distortion Rate (%). Source: github.com. Saturation forecast: Around January 2028. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)16.74#93
2GPT-5.518#48
3Claude Sonnet 4.622.55#159
4Qwen 3.5 397B A17B22.78#245
5Qwen 3.5 Plus22.89#232
6Qwen 3.5 122B A10B23.01#335
7Llama 3.1 8B Instruct24.94#4318
8DeepSeek V4 Pro25.17#188
9DeepSeek V4 Flash25.17#259
10Qwen 3.5 35B A3B25.63#492
11Llama 3.1 70B Instruct25.74#1629

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-goodreads-dual-domain-evidence-distortion · How It Works · Data refreshed daily, snapshot 2026-11-08.