multimodal benchmark
MIMIC-CXR is a large publicly available dataset of chest radiographs with free-text radiology reports. Contains 377,110 images corresponding to 227,835 radiographic studies from 65,379 patients at Beth Israel Deaconess Medical Center. The dataset is de-identified and widely used for medical imaging research, automated report generation, and medical AI development.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | GO | 88.9% | 100.0% | 1 | C |
The leading models and scores on this benchmark.
What MIMIC CXR measures and how its scores work.
MIMIC-CXR is a large publicly available dataset of chest radiographs with free-text radiology reports. Contains 377,110 images corresponding to 227,835 radiographic studies from 65,379 patients at Beth Israel Deaconess Medical Center. The dataset is de-identified and widely used for medical imaging research, automated report generation, and medical AI development.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about MIMIC CXR.
MedGemma 4B IT is currently ranked first with 88.9%.
MIMIC-CXR is a large publicly available dataset of chest radiographs with free-text radiology reports. Contains 377,110 images corresponding to 227,835 radiographic studies from 65,379 patients at Beth Israel Deaconess Medical Center. The dataset is de-identified and widely used for medical imaging research, automated report generation, and medical AI development.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.