Cortex.dev vs Tensorflow Lite

Cortex.dev vs Tensorflow Lite: What are the differences?

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; Tensorflow Lite: Deploy machine learning models on mobile and IoT devices. It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

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

Some of the features offered by Cortex.dev are:

• Autoscaling
• Supports TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, and more
• CPU / GPU support

On the other hand, Tensorflow Lite provides the following key features:

• Lightweight solution for mobile and embedded devices
• Enables low-latency inference of on-device machine learning models with a small binary size
• Fast performance

Cortex.dev is an open source tool with 3.92K GitHub stars and 300 GitHub forks. Here's a link to Cortex.dev's open source repository on GitHub.