CardioLens: leaderboard
Multimodal Large Language Models (MLLMs) have shown strong performance on public medical benchmarks, yet existing evaluations often remain weak proxies for clinical use, relying on isolated inputs and simplified recognition-style tasks. We introduce CardioLens, a leakage-resistant evaluation testbed for multi-sequence Cardiovascular Magnetic Resonance (CMR), constructed from private hospital archi
Metric: F1 (Random) (self-reported). Source: benchmarklist.com. 24 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemma 3 27B | 51.77 | #607 |
| 2 | Gemma 4 31B | 51.61 | #200 |
| 3 | MedGemma-4B | 51.53 | #746 |
| 4 | GPT-5 | 49.21 | #98 |
| 5 | Claude Opus 4.6 | 45.55 | #63 |
| 6 | Gemini 3.1 Pro (Preview) | 44.41 | #58 |
| 7 | Llama 3.2 11B | 41.01 | #1199 |
| 8 | phi-4-14B | 36.4 | #733 |
Interactive version: theaggregate.ai/benchmark?slug=cardiolens · How It Works · Data refreshed daily, snapshot 2026-10-20.