SPUR - Heterogeneous Integration: leaderboard
Metric: Accuracy (%) on SPUR the 130 heterogeneous integration 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 align and reason across panels of different types; higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 20 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Ministral-3-14B-Instruct-2512 | 70 |
| 2 | GLM-4.5V | 68.46 |
| 3 | Ministral-3-8B-Instruct-2512 | 66.15 |
| 4 | Qwen 3 VL 30B A3B Instruct | 63.08 |
| 5 | Qwen 2.5 VL 72B Instruct | 61.9 |
| 6 | Gemini 2.5 Pro (Preview 06-05) | 61.54 |
| 7 | InternVL3-78B | 61.24 |
| 8 | Qwen 3 VL 30B A3B (Thinking) | 61.24 |
| 9 | Claude 3.7 Sonnet (Thinking) | 60.8 |
| 10 | Gemini 3 Pro (Preview) | 59.23 |
| 11 | O4 Mini (High) | 59.23 |
| 12 | Llama 4 Maverick | 58.46 |
| 13 | Gemma 3 27B (IT) | 57.69 |
| 14 | Mistral Small 3.1 | 56.92 |
| 15 | Seed-1.6 | 56.92 |
Interactive version: theaggregate.ai/benchmark?slug=spur-heterogeneous-integration · How It Works · Data refreshed daily, snapshot 2026-10-07.