Apache MXNet is an open-source deep learning framework that is lightweight, memory-efficient, and highly performant. It is known for its ability to work on CPUs and GPUs.

MXNet is also portable to smart devices via its cross-compilation on ARM. Its NumPy-like interface integrates with Gluon 2.0 and supports parallelism through BytePS, Horovod, and ps-lite.

Project Background

  • Framework: Apache MXNet
  • Author: Carlos Guestrin
  • Stable Release: March 2021
  • Type: Open-source library for deep learning
  • License: Apache License 2.0
  • Contains:, GluonCV, GluonNLP, GluonTS, 8 language bindings, distributed training, etc.
  • Language: C++, Python, R, Java, Julia, JavaScript, Scala, Go, Perl
  • GitHub: incubator-mxnet┬áhas 19.7k stars and 864 contributors
  • Runs On: Windows, macOS, Linux
  • Twitter: MXNet
  • Stackflow: MXNet


  • Simplifying common expressions
  • Design deep neural networks
  • Faster computation
  • Accelerate numerical computation
  • Face recognition
  • Machine translation
  • Optical character recognition
  • Long short-term memory networks
  • Convolutional neural networks (CNNs)
  • Exploration and experimentation
  • Scale to multiple GPUs
  • Augmented reality and scene identification
  • Translate voice conversations into text

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