MMJailBench - Hate & Harassment: leaderboard

MMJailBench (Wang et al., 2026) is a factorized multimodal jailbreak benchmark: 272 harmful intents crossed with six prompt framings, five task-relevant visual contexts and text or in-image instructions, 16,320 instances per model. This board covers the Hate & Harassment domain (hate-speech, extremism and harassment requests) across all framings, visual contexts and carriers. Attack success rate in percent, the share of responses a GPT-5 judge scores 4 or 5 on a 1-5 harmfulness rubric; lower is better.

Metric: Attack success rate (%; share of responses a GPT-5 judge scores 4 or 5 on a 1-5 harmfulness rubric; Hate & Harassment domain, 30 harmful intents across all framings, visual contexts and carriers). Source: arxiv.org. Saturation forecast: Estimated already saturated. 16 models tracked.

Top models

#ModelScoreOverall rank
1GPT-52.5#163
2Claude Sonnet 4.57#244
3Gemini 3 Flash28.72#159
4Kimi K2.534#252
5InternVL3-8B42.33#1695
6Ministral 3 8B43.11#2036
7Seed 2.0 Lite47.5#286
8Grok 4 Fast49.33#438
9Qwen 2.5 VL 7B Instruct54.39#1842
10Gemma 3 12B62.67#2013
11GLM-4.6V74.94#698

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=mmjailbench-hate-harassment · How It Works · Data refreshed daily, snapshot 2026-11-12.