Flexible

Supports both imperative and symbolic programming

Portable

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

Multiple Languages

Supports multiple languages, including C++, Python, R, Scala, Julia, Matlab and Javascript - All with the same amazing performance.

Auto-Differentiation

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

Performance

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).