CureMed-Bench - Language Consistency: leaderboard

Target-language fidelity on CureMed-Bench (Onyame et al., 2026): the share of final answers written in the language of the question, pooled over 1,431 held-out open-ended medical questions in 13 languages, zero-shot. Scored separately from correctness, in percent; higher is better.

Metric: Language consistency (%; share of final answers written in the language of the question, pooled over 1,431 held-out open-ended medical questions in 13 languages; zero-shot). Source: arxiv.org. Saturation forecast: Estimated already saturated. 49 models tracked.

Top models

#ModelScoreOverall rank
1Claude 3 Haiku93.43#2629
2Llama 3.3 70B Instruct79.66#1353
3Llama 3.1 70B75.68#1493
4GPT-5 Mini75.33#349
5Qwen 2.5 72B Instruct70.73#1093
6GPT-5 Nano69.11#888
7Qwen 3 32B55.83#960
8Gemini 2.5 Flash48.01#452
9Llama 3 8B UltraMedical47.03#6117
10Ministral 8B46.93#4511
11Qwen 3 14B43.71#1235
12Qwen 2.5 32B Instruct41.51#1216
13Llama 3.1 8B Instruct36.56#4277
14Qwen 2.5 14B Instruct35.57#1745
15Qwen 3 8B33.96#1838

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

Interactive version: theaggregate.ai/benchmark?slug=curemed-bench-language-consistency · How It Works · Data refreshed daily, snapshot 2026-11-12.