Leaf vs Cortex.dev: What are the differences?

Leaf: Machine learning framework in Rust. Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack; Cortex.dev: Deploy machine learning models in production. It is an open source platform that takes machine learning models—trained with nearly any framework—and turns them into production web APIs in one command.

Leaf and Cortex.dev can be categorized as "Machine Learning" tools.

Leaf and Cortex.dev are both open source tools. Leaf with 5.42K GitHub stars and 270 forks on GitHub appears to be more popular than Cortex.dev with 1.42K GitHub stars and 69 GitHub forks.