Confidence Decision Faithfulness - HLE - Policy Consistency: leaderboard

Whether decisions follow verbal confidence when errors incur penalties. The original paper averages all reported penalty levels within each task. Policy consistency and penalty-normalized regret stay separate; theoretical threshold-policy utility is not an observed model result. Original 0-1 units retained. This series reports Policy Consistency (0-1). Source: https://arxiv.org/html/2601.07767v1.

Metric: Policy Consistency (0-1). Source: arxiv.org. 10 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 Next 80B A3B (Thinking)0.82#312
2Gemini 2.5 Flash0.81#255
3Gemma 3n E4B (IT)0.78#747
4Gemini 3 Flash0.77#103
5DeepSeek V3.2 (Non-reasoning)0.72#210 (DeepSeek V3.2)
6Llama 4 Maverick0.71#486
7GPT-4.1 Mini0.69#363
8GPT-5 Mini0.66#193
9DeepSeek V3.2 (Thinking)0.66#210 (DeepSeek V3.2)
10GPT-5 Nano0.58#439

Interactive version: theaggregate.ai/benchmark?slug=confidence-decision-faithfulness-hle-policy-consistency · How It Works · Data refreshed daily, snapshot 2026-11-05.