Propel vs Gradio: What are the differences?

Developers describe Propel as "Machine learning for JavaScript". Propel provides a GPU-backed numpy-like infrastructure for scientific computing in JavaScript. On the other hand, Gradio is detailed as "*GUIs for Faster ML Prototyping and Sharing *". It allows you to quickly create customizable UI components around your TensorFlow or PyTorch models, or even arbitrary Python functions. Mix and match components to support any combination of inputs and outputs.

Propel and Gradio can be categorized as "Machine Learning" tools.

Some of the features offered by Propel are:

• Run anywhere, in the browser or natively from Node
• Target multiple GPUs and make TCP connections
• PhD optional

On the other hand, Gradio provides the following key features:

• Customizable Components
• Multiple Inputs and Outputs
• Sharing Interfaces Publicly & Privacy

Propel is an open source tool with 2.78K GitHub stars and 79 GitHub forks. Here's a link to Propel's open source repository on GitHub.