Caffe2 vs MXNet: What are the differences?

Developers describe Caffe2 as "Open Source Cross-Platform Machine Learning Tools (by Facebook)". Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile. On the other hand, MXNet is detailed as "A flexible and efficient library for deep learning". A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.

Caffe2 and MXNet can be primarily classified as "Machine Learning" tools.

Caffe2 and MXNet are both open source tools. MXNet with 17.5K GitHub stars and 6.21K forks on GitHub appears to be more popular than Caffe2 with 8.46K GitHub stars and 2.12K GitHub forks.