RPCBench - Error Group - Underspecified Premise - Composite Premise Critique: leaderboard

RPCBench tests proactive premise critique in recommendation requests. This series measures composite premise critique on the Underspecified Premise subset (1,300 questions), using the same eleven-model, three-judge experiment as the headline paper. Published CPCC fractions from the authors' per-model CSV are scaled once to Composite Score (0-100). Higher is better; domains and nested premise-error groups are related slices of the same experiment.

Metric: Composite Score (0-100). Source: github.com. Saturation forecast: Around 2031. 11 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek V4 Pro9.13#113
2Claude Sonnet 4.67.32#97
3Qwen 3.5 35B A3B7.32#270
4Gemini 3.1 Pro (Preview)7.19#66
5Qwen 3.5 122B A10B6.57#186
6DeepSeek V4 Flash6.45#156
7Qwen 3.5 Plus6.32#136
8Qwen 3.5 397B A17B6.06#155
9GPT-5.54.79#34
10Llama 3.1 8B Instruct2.55#1021
11Llama 3.1 70B Instruct1.77#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-underspecified-premise-composite-premise-critique · How It Works · Data refreshed daily, snapshot 2026-11-07.