Kluster Hallucination Detection - RAG Resistance: leaderboard

The "RAG Resistance" subtask of Kluster Hallucination Detection. A task from the Kluster Hallucination Detection benchmark, measuring how reliably a model detects unsupported or fabricated claims.

Metric: Resistance (100 - Hallucination Rate %). Source: huggingface.co. Saturation forecast: Estimated already saturated. 17 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro98.43#152
2Claude Sonnet 497.79#199
3DeepSeek R1 052897.74#222
4Kimi K297.1#243
5Llama 4 Maverick Instruct FP896.66#414
6Gemma 3 27B (IT)96.29#523
7Llama 4 Scout Instruct95.77#539
8DeepSeek V3 (0324)95.34#340
9Mistral Small 395.26#627
10GPT-4o93.95#343
11Qwen 3 235B A22B FP893.84#301
12Qwen 3 235B A22B 250792.47#260
13Magistral Small91.38#1016
14Qwen 2.5 VL 7B Instruct90.65#654
15Mistral Nemo Instruct (2407)89.37#936

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

Interactive version: theaggregate.ai/benchmark?slug=kluster-hallucination-detection-rag-resistance · How It Works · Data refreshed daily, snapshot 2026-10-20.