tensor-js

What it is

tensor-js is a deep learning library designed to run directly in web browsers. It leverages WebGL for GPU acceleration and WebAssembly for high performance, making it ideal for running complex models on client devices without server-side dependencies.

tensor-js stands out as one of the few deep learning libraries optimized for client-side execution in web browsers, offering a unique blend of performance and accessibility.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited support for advanced deep learning models

   tensor-js lacks native support for complex architectures like transformers or GANs, requiring manual implementation

2. 02

   Performance can degrade on lower-end devices

   WebGL and WebAssembly performance is highly dependent on the device's graphics capabilities and may not be optimal on older hardware

3. 03

   Small community and limited third-party integrations

   Compared to larger frameworks like TensorFlow.js, tensor-js has fewer contributors and less third-party support for tools and libraries

What it does well

• Runs deep learning models directly in the browser

• Accelerated by WebGL and WebAssembly for high performance

• No server-side dependencies required

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.