RPCBench - Error Group - Unverifiable Premise - Evidence Distortion: leaderboard
RPCBench tests proactive premise critique in recommendation requests. This series measures evidence distortion on the Unverifiable Premise subset (1,020 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: Estimated already saturated. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.5 | 3.63 | #34 |
| 2 | Qwen 3.5 397B A17B | 8.53 | #155 |
| 3 | Gemini 3.1 Pro (Preview) | 8.92 | #66 |
| 4 | Qwen 3.5 122B A10B | 9.8 | #186 |
| 5 | Qwen 3.5 35B A3B | 10.29 | #270 |
| 6 | Qwen 3.5 Plus | 10.39 | #136 |
| 7 | DeepSeek V4 Flash | 11.67 | #156 |
| 8 | DeepSeek V4 Pro | 12.06 | #113 |
| 9 | Llama 3.1 8B Instruct | 12.94 | #1021 |
| 10 | Claude Sonnet 4.6 | 13.53 | #97 |
| 11 | Llama 3.1 70B Instruct | 17.45 | #570 |
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-distortion · How It Works · Data refreshed daily, snapshot 2026-11-07.