Netron
Self-HostedOpen-source neural network model visualizer
Overview
Netron is an open-source tool for visualizing neural network, deep learning, and machine learning models. It supports over 100 formats including ONNX, TensorFlow Lite, PyTorch, Keras, and TensorFlow. Features include interactive graph navigation, layer detail inspection, model metadata viewing, and diagram exports (PNG/SVG/PDF). Self-hosting options: Docker (official image), static web server (host built files), or run from source with Node.js. Desktop apps are also available for offline use across Windows, macOS, and Linux.
Key Features
- Supports 100+ model formats (ONNX, TensorFlow, PyTorch)
- Interactive graph visualization with layer details
- Self-hostable via Docker or static web server
- Export diagrams to PNG/SVG/PDF formats
Frequently Asked Questions
? Is Netron hard to install?
Netron is easy to self-host: use the official Docker image (docker run -p 8080:8080 lutzroeder/netron) or host static files on any server. Desktop versions are downloadable directly (no setup). Source installation needs Node.js and npm/yarn.
? Is it a good alternative to TensorBoard?
Netron shines for cross-framework model architecture visualization (100+ formats), while TensorBoard is TensorFlow-centric with training metrics. For multi-framework models (PyTorch + ONNX), Netron is better; for TensorFlow training analytics, TensorBoard is more suitable.
? Is it completely free?
Yes! Netron is under the MIT Open Source License, so it’s free to use, modify, and self-host without any costs or restrictions.
Top Alternatives
Tool Info
Pros
- ⊕ Privacy-focused (local model processing)
- ⊕ No subscription fees (MIT licensed)
- ⊕ Cross-platform (web, desktop, mobile)
- ⊕ Regular updates with new format support
Cons
- ⊖ Requires basic server setup for self-hosting
- ⊖ Limited to model visualization (no training analytics)
- ⊖ Some rare model formats may have partial support