Supports both imperative and symbolic programming


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

Multiple Languages

Supports C++, Python, R, Scala, Julia, Perl, Matlab and Javascript - All with the same amazing performance


Calculates the gradients automatically for training a model

Distributed on Cloud

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


Optimized C++ backend engine parallelizes both I/O and computation

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