Intel.ML.OnnxRuntime.OpenVino 1.24.1

Prefix Reserved 
dotnet add package Intel.ML.OnnxRuntime.OpenVino --version 1.24.1
                    


                    

                
NuGet\Install-Package Intel.ML.OnnxRuntime.OpenVino -Version 1.24.1
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="Intel.ML.OnnxRuntime.OpenVino" Version="1.24.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="Intel.ML.OnnxRuntime.OpenVino" Version="1.24.1" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="Intel.ML.OnnxRuntime.OpenVino" />
                    


                            Project file
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 Intel.ML.OnnxRuntime.OpenVino --version 1.24.1
                    


                    

                
#r "nuget: Intel.ML.OnnxRuntime.OpenVino, 1.24.1"
#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. 
#:package Intel.ML.OnnxRuntime.OpenVino@1.24.1
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package. 
#addin nuget:?package=Intel.ML.OnnxRuntime.OpenVino&version=1.24.1
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=Intel.ML.OnnxRuntime.OpenVino&version=1.24.1
                    


                            Install as a Cake Tool

About

ONNX Runtime Logo

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
Microsoft.ML.OnnxRuntime.Gpu
Microsoft.ML.OnnxRuntime.DirectML
Microsoft.ML.OnnxRuntime.QNN
Intel.ML.OnnxRuntime.OpenVino

Other packages

Microsoft.ML.OnnxRuntime.Managed
  • C# language bindings
Microsoft.ML.OnnxRuntime.Extensions
There are no supported framework assets in this package.

Learn more about Target Frameworks and .NET Standard.

NuGet packages (1)

Showing the top 1 NuGet packages that depend on Intel.ML.OnnxRuntime.OpenVino:

Package Downloads
YoloDotNet.ExecutionProvider.OpenVino

YoloDotNet OpenVINO Execution Provider enables optimized inference using Intel® OpenVINO™ on supported Intel CPUs, integrated GPUs, and accelerators. This execution provider integrates ONNX Runtime with Intel OpenVINO to deliver high-performance, low-latency inference on Intel hardware across Windows and Linux. It is ideal for CPU-focused deployments, edge systems, and environments where Intel hardware acceleration is preferred over CUDA-based solutions. The provider is fully modular and designed to work with the execution-provider-agnostic YoloDotNet core library introduced in v4.0. Only one execution provider should be referenced per project.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
1.24.1 207 2/26/2026
1.23.0 2,832 10/15/2025
1.22.0 2,806 5/26/2025 1.22.0 is deprecated because it is no longer maintained.
1.21.0 721 4/9/2025
1.20.0 3,124 12/10/2024

Release Def:
Branch:
Commit:
Build: https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=