ONNX

Move a model between frameworks and runtimes

ML frameworks & MLOpsModel interchangeApache-2.0Runs locallyPythonIntermediate

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What is ONNX?

ONNX is the common format that lets a model trained in PyTorch run in a C++ runtime, on mobile, or on an edge accelerator.

Why people choose ONNX

Framework-neutral by design
ONNX Runtime is fast on CPU and edge
Backed by the whole industry

ONNX at a glance

Category	ML frameworks & MLOps
Type	Model interchange
License	Apache-2.0
Runs locally	Yes
Built with	Python
Skill level	Intermediate
Best for	deploying a model somewhere its training framework cannot go

Open-source alternatives to ONNX

Other open-source ml frameworks & mlops tools worth comparing:

DagsterOrchestration that thinks in data assets, not tasks

TensorFlowGoogle's deep-learning framework, built for production

PyTorchThe framework nearly every modern AI model is written in

OpenCVThe computer vision library everything else builds on

scikit-learnClassical machine learning, done properly

Apache AirflowSchedule and monitor data pipelines

RayScale Python from a laptop to a cluster

JAXNumPy with autodiff, JIT and TPUs

XGBoostStill the one to beat on tabular data

Label StudioLabel anything — text, images, audio, video

MLflowTrack experiments and ship models without the spreadsheet

LightGBMGradient boosting that trains fast on big tables

CVATSerious annotation for computer vision

DVCGit for datasets and models

OptunaFind the right hyperparameters without guessing

ONNX head-to-head

ONNX vs Dagster ONNX vs TensorFlow ONNX vs PyTorch ONNX vs OpenCV ONNX vs scikit-learn ONNX vs Apache Airflow ONNX vs Ray ONNX vs JAX ONNX vs XGBoost ONNX vs Label Studio ONNX vs MLflow ONNX vs LightGBM ONNX vs CVAT ONNX vs DVC ONNX vs Optuna

FAQ

Is ONNX free?

ONNX is free and open-source (Apache-2.0 license), so you can use, self-host and modify it at no cost.

Can I run ONNX locally?

Yes. ONNX is designed to run on your own machine or server, keeping your data private.

What is the best alternative to ONNX?

Popular open-source alternatives include Dagster, TensorFlow, PyTorch. See the comparisons above to choose.

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