Whisper.net

June 8, 2026 · View on GitHub

Open-Source Whisper.net

Dotnet bindings for OpenAI Whisper made possible by whisper.cpp

Build Status

Build type	Build Status
CI Status (Native + dotnet)

Getting Started

To install Whisper.net with all the available runtimes, run the following command in the Package Manager Console:

    PM> Install-Package Whisper.net.AllRuntimes

Or add a package reference in your .csproj file:

    <PackageReference Include="Whisper.net.AllRuntimes" Version="1.9.1" />

Whisper.net is the main package that contains the core functionality but does not include any runtimes. Whisper.net.AllRuntimes includes all available runtimes for Whisper.net, including both CUDA 13 (Whisper.net.Runtime.Cuda) and CUDA 12 (Whisper.net.Runtime.Cuda12) GPU builds.

Installing Specific Runtimes

To install a specific runtime, you can install them individually and combine them as needed. For example, to install the CPU runtime, add the following package references:

    <PackageReference Include="Whisper.net" Version="1.9.1" />

    <PackageReference Include="Whisper.net.Runtime" Version="1.9.1" />

GPT for Whisper

We also have a custom-built GPT inside ChatGPT, which can help you with information based on this code, previous issues, and releases. Available here.

Please try to ask it before publishing a new question here, as it can help you a lot faster.

Runtimes Description

Whisper.net comes with multiple runtimes to support different platforms and hardware acceleration. Below are the available runtimes:

Whisper.net.Runtime

The default runtime that uses the CPU for inference. It is available on all platforms and does not require any additional dependencies.

Examples:

Pre-requisites

Windows: Microsoft Visual C++ Redistributable for at least Visual Studio 2022 (x64) Download Link
Windows 11 or Windows Server 2022 (or newer) is required
Linux: libstdc++6, glibc 2.31
macOS: TBD
For x86/x64 platforms, the CPU must support AVX, AVX2, FMA and F16C instructions. If your CPU does not support these instructions, you'll need to use the Whisper.net.Runtime.NoAvx runtime instead.

Supported Platforms

Windows x86, x64, ARM64
Linux x64, ARM64, ARM
macOS x64, ARM64 (Apple Silicon)
Android
iOS
MacCatalyst
tvOS
WebAssembly

Whisper.net.Runtime.NoAvx

For CPUs that do not support AVX instructions.

Pre-requisites

Windows: Microsoft Visual C++ Redistributable for at least Visual Studio 2022 (x64) Download Link
Windows 11 or Windows Server 2022 (or newer) is required
Linux: libstdc++6, glibc 2.31
macOS: TBD

Supported Platforms

Windows x86, x64, ARM64
Linux x64, ARM64, ARM

Whisper.net.Runtime.Cuda

Contains the native whisper.cpp library with NVidia CUDA support enabled (built with the CUDA 13 toolchain).

Examples

CUDA usage example

Pre-requisites

Everything from Whisper.net.Runtime pre-requisites
NVidia GPU with CUDA support
CUDA Toolkit (>= 13.0.1)

Supported Platforms

Windows x64
Linux x64

Whisper.net.Runtime.Cuda12

Contains the native whisper.cpp library with NVidia CUDA support enabled, built against the CUDA 12 toolchain for systems that only provide CUDA 12.x drivers.

Examples

CUDA usage example

Pre-requisites

Everything from Whisper.net.Runtime pre-requisites
NVidia GPU with CUDA support
CUDA Toolkit (>= 12.4.1)

Supported Platforms

Windows x64
Linux x64

Whisper.net.Runtime.CoreML

Contains the native whisper.cpp library with Apple CoreML support enabled.

Examples:

CoreML example

Supported Platforms

macOS x64, ARM64 (Apple Silicon)
iOS
MacCatalyst

Whisper.net.Runtime.OpenVino

Contains the native whisper.cpp library with Intel OpenVino support enabled.

Examples

OpenVino Example

Pre-requisites

Everything from Whisper.net.Runtime pre-requisites
OpenVino Toolkit (>= 2024.4)

Supported Platforms

Windows x64
Linux x64

Whisper.net.Runtime.Vulkan

Contains the native whisper.cpp library with Vulkan support enabled.

Examples

Vulkan Example

Pre-requisites

Everything from Whisper.net.Runtime pre-requisites
Vulkan Toolkit (>= 1.4.321.1)]

Supported Platforms

Windows x64

Multiple Runtimes Support

You can install and use multiple runtimes in the same project. The runtime will be automatically selected based on the platform you are running the application on and the availability of the native runtime.

The following order of priority will be used by default:

Whisper.net.Runtime.Cuda (NVidia devices with CUDA 13 drivers installed)
Whisper.net.Runtime.Cuda12 (NVidia devices with CUDA 12 drivers installed)
Whisper.net.Runtime.Vulkan (Windows x64 with Vulkan installed)
Whisper.net.Runtime.CoreML (Apple devices)
Whisper.net.Runtime.OpenVino (Intel devices)
Whisper.net.Runtime (CPU inference)
Whisper.net.Runtime.NoAvx (CPU inference without AVX support)

The loader automatically probes the CUDA runtimes in this order and validates the installed driver via cudaRuntimeGetVersion, so machines with only CUDA 12 drivers will transparently fall back to Whisper.net.Runtime.Cuda12.

To change the order or force a specific runtime, set the RuntimeLibraryOrder on the RuntimeOptions:

RuntimeOptions.RuntimeLibraryOrder =
[
    RuntimeLibrary.CoreML,
    RuntimeLibrary.OpenVino,
    RuntimeLibrary.Cuda,
    RuntimeLibrary.Cuda12,
    RuntimeLibrary.Cpu
];

Pluggable native runtimes

Whisper.net can run with any compatible compilation of the native whisper.cpp libraries; the package Whisper.net.Runtime is just one of the possible builds we publish.
You may build your own native binaries (CPU, CUDA, CoreML, OpenVINO, Vulkan, NoAvx) and use them with Whisper.net as long as their files are arranged under ./runtimes in the same layout as our NuGet packages. The NativeLibraryLoader will probe them at runtime.
For reproducible builds, you can use the attached GitHub workflows as references or entry points to produce artifacts: .github/workflows/ (e.g., dotnet.yml, dotnet-noavx.yml, dotnet-maui.yml). These workflows compile and package native libraries across platforms and can be adapted for your needs.

Versioning

Whisper.net follows semantic versioning.

Starting from version 1.8.0, Whisper.net does not follow the same versioning scheme as whisper.cpp, which creates releases based on specific commits in their master branch (e.g., b2254, b2255).

To track the whisper.cpp version used in a specific Whisper.net release, you can check the whisper.cpp submodule. The commit hash for the tag associated with the release will indicate the corresponding whisper.cpp version.

Ggml Models

Whisper.net uses Ggml models to perform speech recognition and translation. You can find more about Ggml models here.

For easier integration, Whisper.net provides a Downloader using Hugging Face.

var modelName = "ggml-base.bin";
if (!File.Exists(modelName))
{
    using var modelStream = await WhisperGgmlDownloader.Default.GetGgmlModelAsync(GgmlType.Base);
    using var fileWriter = File.OpenWrite(modelName);
    await modelStream.CopyToAsync(fileWriter);
}

The same downloader can fetch the ggml Silero VAD model used by WhisperVadFactory:

var vadModelName = "ggml-silero-v6.2.0.bin";
if (!File.Exists(vadModelName))
{
    using var modelStream = await WhisperGgmlDownloader.Default.GetGgmlSileroVadModelAsync();
    using var fileWriter = File.OpenWrite(vadModelName);
    await modelStream.CopyToAsync(fileWriter);
}

using var vadFactory = WhisperVadFactory.FromPath(vadModelName);

Models can also be supplied from managed sources without writing native code. Use FromStream, FromBuffer, or implement IWhisperModelLoader when the model comes from a custom source:

using var whisperModelStream = await GetWhisperModelStreamAsync();
using var whisperFactory = WhisperFactory.FromStream(whisperModelStream);

using var vadModelStream = await GetVadModelStreamAsync();
using var vadFactory = WhisperVadFactory.FromStream(vadModelStream);

The Silero VAD model can also be built from the whisper.cpp submodule:

python -m venv venv
.\venv\Scripts\Activate.ps1
pip install silero-vad
python .\whisper.cpp\models\convert-silero-vad-to-ggml.py --output .\whisper.cpp\models\silero.bin

The conversion script names the output with the Silero package version, for example silero-v6.2.0-ggml.bin; add it to the Whisper.net Hugging Face repository as vad/ggml-silero-v6.2.0.bin, then create the v4 tag from that commit so the downloader can resolve it.

Environment variables for model downloads

HF_TOKEN
- Optional. If set, Whisper.net will add an Authorization header when downloading models from Hugging Face to avoid rate limiting.
- Example:
  - Bash: export HF_TOKEN=hf_xxx
  - PowerShell: $env:HF_TOKEN = "hf_xxx"

Usage

using var whisperFactory = WhisperFactory.FromPath("ggml-base.bin");

using var processor = whisperFactory.CreateBuilder()
    .WithLanguage("auto")
    .Build();

using var fileStream = File.OpenRead(wavFileName);

await foreach (var result in processor.ProcessAsync(fileStream))
{
    Console.WriteLine($"{result.Start}->{result.End}: {result.Text}");
}

Documentation

You can find the documentation and code samples here.

Development environment setup notes are available in DEVELOPMENT.md.

Running tests

For instructions on running the test suites locally (including required .NET SDKs, optional environment variables like HF_TOKEN), see tests/README.md.

Offline/local alternative: You can run tests fully locally without network by pre-downloading all ggml models required by tests and pointing tests to them via WHISPER_TEST_MODEL_PATH.
MAUI tests use the Dotnet XHarness CLI to drive emulators/simulators. Docs: https://github.com/dotnet/xharness
Native runtimes: By default, tests and are using the locally built native binaries instead, see “Building The Runtime” in DEVELOPMENT.md and ensure the output matches the expected runtimes layout.

License

MIT License. See LICENSE for details.