ReaLM - AdvEDM: leaderboard

ReaLM (2026) is a red-teaming benchmark for physical-world vision-language models on 832 driving, manipulation, grasping, physics, egocentric, diagnostic and scene cases, attacked black-box toward scenario-specific failure targets. This board is the attack success rate under AdvEDM, semantic editing that steers attention toward the target region: the percent of attacked cases answered incorrectly; lower is better.

Metric: Attack success rate (%; share of adversarial cases where the model gives an incorrect, task-relevant answer) under AdvEDM-A (semantic editing that steers attention toward the target region) on the 832 ReaLM physical-world cases (driving, manipulation, grasping, physics, egocentric, diagnostics and scene QA; image, question and ground-truth answer), black-box one-shot evaluation at temperature 0, a Qwen3-8B judge extracting the answer; lower is better. Source: arxiv.org. Saturation forecast: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash36.5#164
2Qwen 3.5 27B38.8#359
3Qwen 3.5 122B A10B39.3#331
4Qwen 3.6 Flash40.9#424
5Kimi K2.541.6#256
6GPT-4.1 Mini43.5#779
7Qwen 3.5 9B43.9#803
8Seed 2.0 Mini44.1#508

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

Interactive version: theaggregate.ai/benchmark?slug=realm-advedm · How It Works · Data refreshed daily, snapshot 2026-11-13.