RPCBench - Error Group - Underspecified Premise - Evidence Faithfulness: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures evidence faithfulness on the Underspecified Premise subset (1,300 questions), using the same eleven-model, three-judge experiment as the headline paper. Published EFI fractions from the authors' per-model CSV are scaled once to Faithfulness Index (%). Higher is better; domains and nested premise-error groups are related slices of the same experiment.

Metric: Faithfulness Index (%). Source: github.com. Saturation forecast: Not forecast. 11 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3.5 35B A3B73.65#270
2Qwen 3.5 122B A10B72.69#186
3Qwen 3.5 397B A17B72.31#155
4GPT-5.572.04#34
5Qwen 3.5 Plus71.54#136
6Gemini 3.1 Pro (Preview)66.12#66
7DeepSeek V4 Flash65.88#156
8DeepSeek V4 Pro64.23#113
9Claude Sonnet 4.657.08#97
10Llama 3.1 70B Instruct44.62#570
11Llama 3.1 8B Instruct39.27#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-error-group-underspecified-premise-evidence-faithfulness · How It Works · Data refreshed daily, snapshot 2026-11-07.