RPCBench - Domain - MIND-small - Evidence Distortion: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures evidence distortion on the MIND-small subset (703 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: Not forecast. 11 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.519.63#34
2Llama 3.1 70B Instruct23.47#570
3Gemini 3.1 Pro (Preview)23.61#66
4Qwen 3.5 397B A17B24.75#155
5Qwen 3.5 122B A10B25.75#186
6Qwen 3.5 35B A3B25.89#270
7Llama 3.1 8B Instruct27.88#1021
8Qwen 3.5 Plus27.88#136
9DeepSeek V4 Flash28.88#156
10Claude Sonnet 4.630.3#97
11DeepSeek V4 Pro30.3#113

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-evidence-distortion · How It Works · Data refreshed daily, snapshot 2026-11-07.