Netron
Visualizer for neural network and machine learning models
33.4k stars 3.2k forks last commit first released MIT
Actively maintained
Last commit 26 Aug 2026.
Netron is a visualizer for neural network, deep learning, and machine learning models. It helps you inspect model graphs and operators to better understand architectures, verify exports, and debug interoperability issues across frameworks.
Key Features
- Interactive visualization of model computation graphs, layers, and connections
- Broad format support including ONNX, TensorFlow Lite, PyTorch, Core ML, Keras, TensorFlow.js, Safetensors, and NumPy
- Experimental support for additional formats such as TorchScript, MLIR, TensorFlow, GGUF, PaddlePaddle, and scikit-learn
- Runs in multiple environments, including a browser-based viewer and a Python package entry point
Use Cases
- Validate and troubleshoot model exports and conversions (for example, to ONNX or TensorFlow Lite)
- Review model structure during development, code reviews, or incident debugging
- Inspect third-party or pretrained models to understand layer composition and data flow
Netron is a practical tool for engineers and researchers who need a fast, format-flexible way to view and analyze model architectures without loading them into a full training environment.
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