Flexible and Efficient Library for Deep Learning


Supports both imperative and symbolic programmings.


Runs on CPUs or GPUs, on clusters, servers, desktops, or mobile phones

Multiple Lanuages

Supports over 7 programming languages, including C++, Python, R, Scala, Julia, Matlab, and Javascripts.


Calculates the gradient automatically for training a model.

Distributed on Cloud

Supports distributed training on multiple CPU/GPU machines, including AWS, GCE, Azure, and Yarn clusters.


The well-optimized C++ backend engine parallelize both I/O and computations

MXNet is developed by collaborators from multiple universities and companies. We sincerely thank the following organizations for supporing MXNet and sponsoring its major developers (alphabetical order).