MedHarm - Refusal Adequacy: leaderboard

MedHarm (2026) is a medical safety benchmark of 1,100 medically framed harmful requests in ten high-risk categories, such as covert poisoning, lethal dosing or weaponized pathogens, which a model should decline or redirect; a grading model scores each response. This board is the mean score in percent for refusals that block the harmful request and explain the reason, with half credit for a bare refusal; higher is better.

Metric: Refusal adequacy (%): mean judge score for refusals that block the requested harm and explain why (a bare refusal scores half); MedHarm: 1,100 high-risk medical queries in ten categories of 110 (covert poisoning, lethal dosing, lethal drug interactions, euthanasia, illegal organ harvesting and live anesthesia, drug abuse, medicalized chemical and biological weapons, date-rape drugs, fetal harm and more), all requests a model should decline or redirect; greedy decoding, 512 new tokens; GPT-5-mini judge (91% agreement with human labels on unsafe responses); higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 15 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.3 Instant99.9#130
2Llama 3.1 8B Instruct98.1#4246
3GPT-5.595.7#49
4Grok 4.392.4#333
5DeepSeek V4 Pro92.1#188
6Qwen 2.5 7B Instruct82.1#2564

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

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