MedConclusion - Writing Style Similarity: leaderboard

Metric: Writing style similarity (judge score 0-100): the model writes a formal academic conclusion (prompt A, no length or style constraint) from the non-conclusion sections of a PubMed structured abstract; a GPT-5.4-mini judge scores it 0-100 against the author-written conclusion, averaged over a random 30K-abstract subset of MedConclusion; temperature 0, at most 1,024 new tokens; higher is better. Source: arxiv.org. Saturation forecast: Around 2029. 15 models tracked.

Top models

#ModelScore
1GPT-5.4 (Non-reasoning)71.21
2Gemini 3.1 Pro (Preview)70.13
3Gemma 3 27B (IT)69.18
4GLM-4.6V68.83
5DeepSeek V3.2 (Non-reasoning)68.21
6Gemma 2 9B (IT)67.42
7MiniMax-M2.166.95
8Llama 3.1 8B Instruct66.69
9Kimi K2 (Thinking)66.36
10Qwen 3 4B 2507 Instruct66.35
11Qwen 2.5 7B Instruct65.74
12Qwen 2.5 VL 7B Instruct64.74
13Llama 3.2 1B Instruct50.69
14DeepSeek R148.06

Interactive version: theaggregate.ai/benchmark?slug=medconclusion-writing-style-similarity · How It Works · Data refreshed daily, snapshot 2026-10-07.