Free tool for Edge AI developers
STM32Cube.AI allows you to optimize and deploy trained Neural Network models from the most popular AI frameworks on any STM32 microcontroller.
The tool is available via a graphical interface in the STM32CubeMX environment as well as in command line. This tool is now also available online in the STM32Cube.AI Developer Cloud.
New in version 8.0
Introducing the support of ONNX Tensor-oriented file format (QDQ)
Update of supported AI framework:
– TensorFlow 2.11
– Keras.io 2.11
– ONNX Runtime 1.12.1
From Neural Networks to STM32 optimized code
Identify the right STM32 MCU for your project and generate the suitable code from your trained Neural Network model
Make the most of your STM32 microcontroller
By optimizing the memory use and the inference time of your AI models, STM32Cube.AI ensures they can easily run on microcontrollers.
STM32Cube.AI is the most efficient free Neural Network code generator for MCU!
space freed-up in FLASH and RAM*
faster inference time*
* versus TensorFlow Lite for microcontroller
STM32 model zoo – Find the best edge AI model
The STM32 AI model zoo is a collection of pre-trained machine learning models that are optimized to run on STM32 microcontrollers. Available on GitHub, this is a valuable resource for anyone looking to add AI capabilities to their STM32-based projects.
– A large collection of application-oriented models ready for re-training
– Scripts to easily retrain any model from user datasets
– Application code examples automatically generated from user AI model
Boost your application
Using AI opens the door to new application possibilities! Discover inspiring real-world examples and use our resources to create your own application.
Get started with STM32Cube.AI
Discover how to optimize your AI Neural Network and create processing libraries for your STM32 project