RPCBench - Error Group - Unverifiable Premise - Evidence Faithfulness: leaderboard
RPCBench tests proactive premise critique in recommendation requests. This series measures evidence faithfulness on the Unverifiable Premise subset (1,020 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: Estimated already saturated. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.5 | 95.93 | #34 |
| 2 | Qwen 3.5 122B A10B | 92.65 | #186 |
| 3 | Gemini 3.1 Pro (Preview) | 91.72 | #66 |
| 4 | Qwen 3.5 35B A3B | 91.62 | #270 |
| 5 | Qwen 3.5 Plus | 91.27 | #136 |
| 6 | Qwen 3.5 397B A17B | 91.03 | #155 |
| 7 | DeepSeek V4 Pro | 86.91 | #113 |
| 8 | DeepSeek V4 Flash | 81.42 | #156 |
| 9 | Claude Sonnet 4.6 | 72.25 | #97 |
| 10 | Llama 3.1 70B Instruct | 26.86 | #570 |
| 11 | Llama 3.1 8B Instruct | 21.37 | #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-unverifiable-premise-evidence-faithfulness · How It Works · Data refreshed daily, snapshot 2026-11-07.