ONNX
LF AI & Data (Linux Foundation)ONNX (Open Neural Network Exchange) is an open standard format and specification for representing machine learning models, defining an extensible computation graph model plus built-in operators and standard data types. It enables interoperability so models can move between frameworks like PyTorch, TensorFlow, and scikit-learn. It is governed under the Linux Foundation as part of LF AI & Data.
Verified 2026-08-13 via GitHub and the LICENSE body.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core-gated
- ungated
Apache-2.0 license body confirmed; full source public on GitHub. The repository is public and unarchived, and the README describes the whole library with no paid, enterprise or hosted tier beside it, so source is public and the core ungated.
- https://github.com/onnx/onnx/blob/main/LICENSE recorded 2026-08-13
LICENSE file is the verbatim Apache License Version 2.0 text
- https://api.github.com/repos/onnx/onnx recorded 2026-08-13
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for onnx/onnx.
- https://raw.githubusercontent.com/onnx/onnx/main/README.md recorded 2026-08-13
README describes the open format, computation-graph model and built-in operators as an open ecosystem under LF AI & Data. No paid tier appears.
Adoption
5 high confidence19,619,971 PyPI downloads of `onnx` in the trailing 30 days, which clears the top band of the software usage scale, over 10M a month, level 5. That is the same band other products on this map hold at comparable volume - pydantic-ai at around 31M, llama-index at around 10.18M, and the companion onnxruntime at around 74.7M. ONNX is the de facto cross-framework model-exchange standard. `onnxruntime` is a separate product with its own package, and its downloads are not summed in here.
- https://pepy.tech/projects/onnx recorded 2026-08-13
19,619,971 downloads in the last 30 days for onnx
Capability
5 high confidenceDefines the graph model, operators, and data types used as the de-facto interchange standard.
- https://github.com/onnx/onnx recorded 2026-08-13
README still describes an open format with an extensible computation graph and built-in operators as a cross-framework interchange standard
Verified 2026-08-13