MedMNIST was released by Shanghai Jiao Tong University on October 28, 2020. It is a collection of 10 public medical datasets, containing a total of 450,000 28*28 medical multimodal image data, which can be used to solve problems related to medical image analysis. Click to view related papers Click to visit the open source address MedMNIST has the following characteristics: **Educational:**The multimodal data comes from multiple public medical image datasets and uses the Creative Commons (CC) license agreement to facilitate teaching use. **standardization:**All data has been preprocessed into the same format, lowering the entry barrier and making it available to anyone. **Diversity:**The multimodal dataset covers different data modes, supports data sizes ranging from 100 to 100,000, and has rich task types such as binary classification, multivariate classification, ordinal regression, and multi-label. **Lightweight:**The 28*28 image size facilitates rapid prototyping, fast iteration and experimentation of multimodal machine learning and AutoML algorithms.