Home Projects netron
netron
JavaScript

netron

Visualizer for neural network, deep learning and machine learning models

by lutzroeder · GitHub
Top 5% most starred in the catalogue
Stars
Forks
License
2010
Created
Last commit
Category
Language
aicoremldeep-learningMITJavaScript
View on GitHub
In plain words

View and analyze various machine learning models visually to understand their structure and functionality.

From the README

Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
netron — GitHub preview card
📈 Star history
33.2k33.1k
2026-06-272026-08-31
📈 Track netron

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

Visualizer for neural network, deep learning and machine learning models

netron has 33.2k stars on GitHub. It has been forked 3.2k times. netron is written mainly in JavaScript. It has been in active development since 2010. netron is available under the MIT license. Its main topics are ai, coreml, deep-learning, deeplearning.

Frequently asked questions

What is netron?

Visualizer for neural network, deep learning and machine learning models

Is netron open source?

netron is an open-source project. It is released under the MIT license.

Is netron free?

Yes. netron is free and open source — you can use, modify and self-host it.

What license does netron use?

netron is available under the MIT license.

What language is netron written in?

netron is written mainly in JavaScript.

🏅 Maintainer of this project?
olud.ai badge — netron

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=lutzroeder-netron)](https://olud.ai/project/lutzroeder-netron.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.