Microsoft.ML.OnnxRuntime
1.22.0-dev-20250402-1105-67216c8996
Prefix Reserved
.NET 8.0
This package targets .NET 8.0. The package is compatible with this framework or higher.
.NET Standard 2.0
This package targets .NET Standard 2.0. The package is compatible with this framework or higher.
This is a prerelease version of Microsoft.ML.OnnxRuntime.
There is a newer prerelease version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package Microsoft.ML.OnnxRuntime --version 1.22.0-dev-20250402-1105-67216c8996
NuGet\Install-Package Microsoft.ML.OnnxRuntime -Version 1.22.0-dev-20250402-1105-67216c8996
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Microsoft.ML.OnnxRuntime" Version="1.22.0-dev-20250402-1105-67216c8996" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.ML.OnnxRuntime" Version="1.22.0-dev-20250402-1105-67216c8996" />
<PackageReference Include="Microsoft.ML.OnnxRuntime" />
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add Microsoft.ML.OnnxRuntime --version 1.22.0-dev-20250402-1105-67216c8996
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.ML.OnnxRuntime, 1.22.0-dev-20250402-1105-67216c8996"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
#addin nuget:?package=Microsoft.ML.OnnxRuntime&version=1.22.0-dev-20250402-1105-67216c8996&prerelease
#tool nuget:?package=Microsoft.ML.OnnxRuntime&version=1.22.0-dev-20250402-1105-67216c8996&prerelease
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
About
ONNX Runtime is a cross-platform machine-learning inferencing accelerator.
ONNX Runtime can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms.
Learn more → here
NuGet Packages
ONNX Runtime Native packages
Microsoft.ML.OnnxRuntime
- Native libraries for all supported platforms
- CPU Execution Provider
- CoreML Execution Provider on macOS/iOS
- XNNPACK Execution Provider on Android/iOS
Microsoft.ML.OnnxRuntime.Gpu
- Windows and Linux
- TensorRT Execution Provider
- CUDA Execution Provider
- CPU Execution Provider
Microsoft.ML.OnnxRuntime.DirectML
- Windows
- DirectML Execution Provider
- CPU Execution Provider
Microsoft.ML.OnnxRuntime.QNN
- 64-bit Windows
- QNN Execution Provider
- CPU Execution Provider
Intel.ML.OnnxRuntime.OpenVino
- 64-bit Windows
- OpenVINO Execution Provider
- CPU Execution Provider
Other packages
Microsoft.ML.OnnxRuntime.Managed
- C# language bindings
Microsoft.ML.OnnxRuntime.Extensions
- Custom operators for pre/post processing on all supported platforms.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-android31.0 is compatible. net8.0-browser was computed. net8.0-ios was computed. net8.0-ios15.4 is compatible. net8.0-maccatalyst was computed. net8.0-maccatalyst14.0 is compatible. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. net9.0 was computed. net9.0-android was computed. net9.0-browser was computed. net9.0-ios was computed. net9.0-maccatalyst was computed. net9.0-macos was computed. net9.0-tvos was computed. net9.0-windows was computed. |
| .NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 is compatible. |
| .NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| native | native is compatible. |
| Tizen | tizen40 was computed. tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
.NETCoreApp 0.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
-
.NETFramework 0.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
-
.NETStandard 0.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
-
net8.0-android31.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
-
net8.0-ios15.4
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
-
net8.0-maccatalyst14.0
- Microsoft.ML.OnnxRuntime.Managed (>= 1.22.0-dev-20250402-1105-67216c8996)
GitHub repositories (18)
Showing the top 18 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntime:
| Repository | Stars |
|---|---|
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microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
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rocksdanister/lively
Free and open-source software that allows users to set animated desktop wallpapers and screensavers powered by WinUI 3.
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dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
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stakira/OpenUtau
Open singing synthesis platform / Open source UTAU successor
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Webreaper/Damselfly
Damselfly is a server-based Photograph Management app. The goal of Damselfly is to index an extremely large collection of images, and allow easy search and retrieval of those images, using metadata such as the IPTC keyword tags, as well as the folder and file names. Damselfly includes support for object/face detection.
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wangfreexx/wangfreexx-tianruoocr-cl-paddle
天若ocr开源版本的本地版，采用Chinese-lite和paddleocr识别框架
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codeproject/CodeProject.AI-Server
CodeProject.AI Server is a self contained service that software developers can include in, and distribute with, their applications in order to augment their apps with the power of AI.
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rocksdanister/weather
Windows native weather app powered by DirectX12 animations
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microsoft/psi
Platform for Situated Intelligence
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redis/redis-om-dotnet
Object mapping, and more, for Redis and .NET
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dme-compunet/YoloSharp
🚀 Use YOLO11 in real-time for object detection tasks, with edge performance ⚡️ powered by ONNX-Runtime.
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techwingslab/yolov5-net
YOLOv5 object detection with C#, ML.NET, ONNX
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microsoft/CryptoNets
CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic E
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unoplatform/Uno.Samples
A collection of code samples for the Uno Platform
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Azure/azure-stream-analytics
Azure Stream Analytics
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FaceONNX/FaceONNX
Face recognition and analytics library based on deep neural networks and ONNX runtime
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Vincentzyx/VinXiangQi
Xiangqi syncing tool based on Yolov5 / 基于Yolov5的中国象棋连线工具
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deepakkumar1984/MxNet.Sharp
.NET Standard bindings for Apache MxNet with Imperative, Symbolic and Gluon Interface for developing, training and deploying Machine Learning models in C#. https://mxnet.tech-quantum.com/
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Release Def:
Branch: refs/heads/main
Commit: 67216c89965731898a252b23cbcc681a0465c540
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=737901