Image classification STM32 model zoo

January 22, 2026 · View on GitHub

Models are stored depending on the way they have been trained :

ST_pretrainedmodel_public_dataset folder contains models trained by ST using public datasets
ST_pretrainedmodel_custom_dataset folder contains models trained by ST using custom datasets
Public_pretrainedmodel_public_dataset folder contains public models using public datasets

List of available models families:

Following is the overview of all pretrained image classification models available for STM32 boards. Each model family links to its folder or README for downloads, usage, and performance metrics.

TensorFlow Models

Model performance analysis (TF) of these models can be used to select the model based on user's performance requirements.

EfficientNet

FD MobileNet

FDMobileNet

MobileNet

ResNet

SqueezeNet

SqueezeNetv1.1

ST MNIST

ST MNISTv1

PyTorch Models

Model performance analysis (Pytorch) of these models can be used to select the model based on user's performance requirements.

Note: Some folders may contain multiple model variants (Float / Int8, different input resolutions, etc.). For detailed performance tables and ONNX links, refer to the individual README of each model family.