Netron review 2026: the free, open-source neural network model visualizer for ONNX, PyTorch, TensorFlow and more. See features and alternatives.
Netron is a free, open-source visualizer for neural network, deep learning, and machine learning model files, created and maintained by independent developer Lutz Roeder. It renders a model's computation graph as an explorable diagram, showing layers, operators, tensor shapes, and attributes.
Netron should not be confused with networking or infrastructure tools; despite the similar-sounding name, it is a machine learning developer utility, distinct from tools like NetBox that manage physical network infrastructure. It is distributed as a hosted web app at netron.app, a native desktop app for macOS, Windows, and Linux, and a Python package.
Netron's central strength is breadth of format support: it natively handles ONNX, TensorFlow Lite, PyTorch, TorchScript, TensorFlow, Core ML, OpenVINO, Keras, Caffe, Darknet, Safetensors, and NumPy files, with experimental support for formats like MLIR, JAX, GGUF, RKNN, ncnn, MNN, and PaddlePaddle.
Because the browser-based version runs entirely client-side, model files are never uploaded to a server, which matters for teams working with proprietary or sensitive model architectures. The interface lets users zoom, search, and inspect individual layers and tensor shapes interactively.
Netron is completely free and open source under the MIT license, with no paid tiers, subscriptions, or usage limits across the web app, desktop app, or Python package.
As a community project maintained primarily by one developer, support comes through GitHub issues and community contributions rather than a commercial support contract.
Netron is used to visualize the architecture of neural network and machine learning models, showing layers, operators, and tensor shapes as an explorable graph.
Yes, Netron is completely free and open source under the MIT license, with no paid tiers.
Netron was created and is maintained by independent developer Lutz Roeder.
Netron natively supports ONNX, TensorFlow Lite, PyTorch, TorchScript, TensorFlow, Core ML, OpenVINO, Keras, Caffe, Darknet, Safetensors, and NumPy, plus experimental support for formats like MLIR, JAX, and GGUF.
No, Netron is available as a browser-based web app at netron.app that requires no installation, though desktop apps and a Python package are also available.
No, Netron is a machine learning model visualizer, while NetBox is an unrelated open-source tool for network infrastructure documentation and IP address management.
No, the browser-based version of Netron processes model files entirely client-side, so files are never uploaded.