Microsoft.ML.OnnxRuntime.Managed
1.22.0
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.
dotnet add package Microsoft.ML.OnnxRuntime.Managed --version 1.22.0
NuGet\Install-Package Microsoft.ML.OnnxRuntime.Managed -Version 1.22.0
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.Managed" Version="1.22.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="Microsoft.ML.OnnxRuntime.Managed" Version="1.22.0" />
<PackageReference Include="Microsoft.ML.OnnxRuntime.Managed" />
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.Managed --version 1.22.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Microsoft.ML.OnnxRuntime.Managed, 1.22.0"
#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.Managed&version=1.22.0
#tool nuget:?package=Microsoft.ML.OnnxRuntime.Managed&version=1.22.0
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 is compatible. net8.0-android was computed. net8.0-android34.0 is compatible. net8.0-browser was computed. net8.0-ios was computed. net8.0-ios17.2 is compatible. net8.0-maccatalyst was computed. net8.0-maccatalyst17.2 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. net10.0 was computed. net10.0-android was computed. net10.0-browser was computed. net10.0-ios was computed. net10.0-maccatalyst was computed. net10.0-macos was computed. net10.0-tvos was computed. net10.0-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 was computed. |
| .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. |
| 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.
-
.NETStandard 2.0
- System.Memory (>= 4.5.5)
-
net8.0
- System.Memory (>= 4.5.5)
- System.Numerics.Tensors (>= 9.0.0)
-
net8.0-android34.0
- System.Memory (>= 4.5.5)
- System.Numerics.Tensors (>= 9.0.0)
-
net8.0-ios17.2
- System.Memory (>= 4.5.5)
- System.Numerics.Tensors (>= 9.0.0)
-
net8.0-maccatalyst17.2
- System.Memory (>= 4.5.5)
- System.Numerics.Tensors (>= 9.0.0)
NuGet packages (63)
Showing the top 5 NuGet packages that depend on Microsoft.ML.OnnxRuntime.Managed:
| Package | Downloads |
|---|---|
|
Microsoft.ML.OnnxRuntime
This package contains native shared library artifacts for all supported platforms of ONNX Runtime. |
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Microsoft.ML.OnnxRuntime.Gpu
This package contains native shared library artifacts for all supported platforms of ONNX Runtime. |
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Microsoft.ML.OnnxTransformer
ML.NET component for Microsoft.ML.OnnxRuntime.Managed library |
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Microsoft.ML.OnnxRuntime.DirectML
This package contains native shared library artifacts for all supported platforms of ONNX Runtime. |
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Microsoft.ML.OnnxRuntime.Gpu.Linux
This package contains Linux native shared library artifacts for ONNX Runtime with CUDA. |
GitHub repositories (15)
Showing the top 15 popular GitHub repositories that depend on Microsoft.ML.OnnxRuntime.Managed:
| Repository | Stars |
|---|---|
|
dotnet/machinelearning
ML.NET is an open source and cross-platform machine learning framework for .NET.
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babalae/better-genshin-impact
📦BetterGI · 更好的原神 - 自动拾取 | 自动剧情 | 全自动钓鱼(AI) | 全自动七圣召唤 | 自动伐木 | 自动刷本 | 自动采集/挖矿/锄地 | 一条龙 | 全连音游 - UI Automation Testing Tools For Genshin Impact
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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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rocksdanister/weather
Windows native weather app powered by DirectX12 animations
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techwingslab/yolov5-net
YOLOv5 object detection with C#, ML.NET, ONNX
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microsoft/onnxruntime-training-examples
Examples for using ONNX Runtime for model training.
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sstainba/Yolov8.Net
A .net 6 implementation to use Yolov5 and Yolov8 models via the ONNX Runtime
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unoplatform/Uno.Samples
A collection of code samples for the Uno Platform
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cassiebreviu/StableDiffusion
Inference Stable Diffusion with C# and ONNX Runtime
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FaceONNX/FaceONNX
Face recognition and analytics library based on deep neural networks and ONNX runtime
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TensorStack-AI/OnnxStack
C# Stable Diffusion using ONNX Runtime
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guojin-yan/YoloDeployCsharp
Deploying Yolov8-det, Yolov8-pose, Yolov8-cls, and Yolov8-seg models based on C # programming language.
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Particle1904/DatasetHelpers
Dataset Helper program to automatically select, re scale and tag Datasets (composed of image and text) for Machine Learning training.
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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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| Version | Downloads | Last updated | |
|---|---|---|---|
| 1.22.0 | 20,378 | 5/9/2025 | |
| 1.21.2 | 4,147 | 4/24/2025 | |
| 1.21.1 | 2,002 | 4/21/2025 | |
| 1.21.0 | 120,514 | 3/7/2025 | |
| 1.20.2 | 6,643 | 2/11/2025 | |
| 1.20.1 | 396,528 | 11/21/2024 | |
| 1.20.0 | 218,083 | 10/31/2024 | |
| 1.19.2 | 348,524 | 9/3/2024 | |
| 1.19.1 | 36,431 | 8/21/2024 | |
| 1.19.0 | 11,384 | 8/15/2024 | |
| 1.18.1 | 581,633 | 6/27/2024 | |
| 1.18.0 | 113,158 | 5/17/2024 | |
| 1.17.3 | 77,561 | 4/10/2024 | |
| 1.17.1 | 218,123 | 2/25/2024 | |
| 1.17.0 | 186,009 | 1/31/2024 | |
| 1.16.3 | 371,418 | 11/20/2023 | |
| 1.16.2 | 15,323 | 11/9/2023 | |
| 1.16.1 | 61,776 | 10/11/2023 | |
| 1.16.0 | 90,097 | 9/19/2023 | |
| 1.15.1 | 251,986 | 6/16/2023 | |
| 1.15.0 | 39,415 | 5/24/2023 | |
| 1.15.0-rc | 1,361 | 5/17/2023 | |
| 1.15.0-alpha | 1,064 | 5/12/2023 | |
| 1.14.1 | 142,803 | 2/27/2023 | |
| 1.14.0 | 311,898 | 2/10/2023 | |
| 1.13.1 | 164,389 | 10/24/2022 | |
| 1.12.1 | 251,882 | 8/4/2022 | |
| 1.12.0 | 12,300 | 7/22/2022 | |
| 1.11.0 | 236,608 | 3/25/2022 | |
| 1.10.0 | 292,009 | 12/7/2021 | |
| 1.9.0 | 134,371 | 9/22/2021 | |
| 1.8.1 | 116,236 | 7/7/2021 | |
| 1.8.0 | 26,335 | 6/3/2021 | |
| 1.7.1 | 51,392 | 3/4/2021 | |
| 1.7.0 | 113,026 | 3/2/2021 | |
| 1.6.0 | 320,371 | 12/10/2020 | |
| 1.5.2 | 54,914 | 10/15/2020 | |
| 1.5.1 | 15,195 | 9/29/2020 | |
| 1.4.0 | 149,061 | 7/17/2020 | |
| 1.3.0 | 100,265 | 5/18/2020 | |
| 1.2.0 | 86,145 | 3/10/2020 |
Release Def:
Branch: refs/heads/rel-1.22.0
Commit: f217402897f40ebba457e2421bc0a4702771968e
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=781523