Grip on LLMs - HonestCityBench - Insufficient Information: leaderboard

Grip on LLMs (arXiv 2608.09925v1, Appendix Table 2): HonestCityBench, 530 Dutch prompts that a model cannot or should not answer directly. Share of responses judged to appropriately acknowledge that the prompt lacks information needed to answer, percent. Higher is better.

Metric: Appropriate acknowledgement rate (%; LLM judge). Source: arxiv.org. Saturation forecast: Not forecast. 31 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5 Mini60#193
2Mistral Small 356#630
3Qwen 3 8B54#678
4Gemma 3 12B (IT)52#672
5Qwen 3 32B50#449
6Gemma 3 27B (IT)44#528
7OLMo-2-0325-32B-Instruct41#847
8GPT-OSS-20B37#523
9GEITje-7B-ultra35#1435
10Llama 3.1 8B Instruct34#1017
11DeepSeek R1 Distill Qwen 32B34#662
12EuroLLM-9B-Instruct32#1047
13Phi-4 Mini Instruct31#1232
14GPT-4o30#357
15GPT-4o Mini30#598

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=grip-on-llms-honestcitybench-insufficient-information · How It Works · Data refreshed daily, snapshot 2026-11-05.