SPUR - Trend Analysis: leaderboard
Metric: Accuracy (%) on SPUR the 1,357 trend analysis multiple-choice questions about multi-panel biomedical experimental figures from PubMed Central papers (questions drafted by GPT-4o, kept only when GPT-4o failed them in at least six of ten text-only attempts, then expert-reviewed): the questions ask the model to interpret directional changes across panels of the same type; higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 20 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Ministral-3-14B-Instruct-2512 | 57.79 |
| 2 | Ministral-3-8B-Instruct-2512 | 57.49 |
| 3 | GLM-4.5V | 55.71 |
| 4 | Qwen 3 VL 30B A3B (Thinking) | 54.85 |
| 5 | Gemini 2.5 Pro (Preview 06-05) | 53.3 |
| 6 | Llama 4 Maverick | 51.88 |
| 7 | Qwen 2.5 VL 72B Instruct | 51.87 |
| 8 | Mistral Small 3.1 | 51.82 |
| 9 | Claude 3.7 Sonnet (Thinking) | 51.3 |
| 10 | GPT-5.1 | 51.18 |
| 11 | Gemini 3 Pro (Preview) | 51.04 |
| 12 | Qwen 3 VL 30B A3B Instruct | 50.41 |
| 13 | InternVL3-78B | 49.52 |
| 14 | Gemma 3 27B (IT) | 48.59 |
| 15 | O4 Mini (High) | 48.37 |
Interactive version: theaggregate.ai/benchmark?slug=spur-trend-analysis · How It Works · Data refreshed daily, snapshot 2026-10-07.