BAGEL - bioRxiv: leaderboard

Metric: Accuracy (%, times 100) on the 2,183 bioRxiv questions (result interpretation of animal-focused preprints) of BAGEL, closed-book four-option single-answer multiple choice (the source passage is withheld), one unified prompt, greedy decoding with seed 0, a single run per model; questions written by GPT-4o-mini from Wikipedia species articles, GloBI interaction records, bioRxiv preprints and Xeno-canto recordings, options shuffled; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 13 models tracked.

Top models

#ModelScore
1GPT-5.494.41
2Phi-492.44
3Qwen 3 32B (Non-reasoning)91.85
4Qwen 3 14B (Non-reasoning)91.11
5Claude Opus 4.691.07
6Gemma 3 27B (IT)90.98
7Qwen 3 8B (Non-reasoning)89.92
8Qwen 3 4B (Non-reasoning)89.01
9Llama 3.1 8B Instruct88.82
10Mistral 7B Instruct (v0.3)85.57
11gemma-7B85.43
12Qwen 3 0.6B (Non-reasoning)24.05

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