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Netron

Netron is a neural-network and machine-learning model viewer that opens supported model files and displays their architectures through browser, desktop and Python access paths.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Netron — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Netron when a model’s graph and file structure need review outside the training or inference workflow, especially during export comparison or deployment preparation.

Who it is for

  • Machine-learning engineers reviewing exported models
  • Researchers inspecting neural-network structures
  • Development teams comparing model exports across frameworks

Documented uses

  • Inspect the structure of a model file visually
  • Review exports from ONNX, PyTorch, TensorFlow or Core ML workflows
  • Compare model architectures across supported formats
  • Add a visual inspection step before deployment
Before you choose

Requirements & limits

The repository documents browser access, desktop installation for macOS, Linux and Windows, and Python installation with pip. Netron is released under the MIT license.

  • Choose the access route that matches the workflow: browser, desktop or Python.
  • Check whether the model format is listed as supported or experimental.
  • Use the format-specific support list when reviewing exports across ONNX, PyTorch, TensorFlow and Core ML.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install Netron for Python model inspection

Set up the Python package and prepare it to open a specified model file.

Before you start

  • Python environment with pip
  • A model file in a supported format

Steps

  1. Install the package with pip using the command below.

    Documented command
    pip install netron

  2. Run netron [FILE] with the path to the model file, or call netron.start('[FILE]') from Python.

  3. Inspect the model through the Netron viewer.

Expected outcome

A Python-based workflow is configured to open a specified model file for visual inspection.

Guide limitations

  • The source documents invocation but does not specify behavior for unsupported files.
  • MLIR, JAX, GGUF, RKNN, ncnn, MNN, PaddlePaddle and scikit-learn support is identified as experimental.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
1 October 2026
Original website title
lutzroeder/netron · Official homepage title · retained in its source language
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