Install prebuilt packages

Prebuilt ML SDK for Vulkan® packages are distributed as Python wheels through PyPI and as binary tarballs and ZIP files through GitHub releases for Linux, Windows®, and Darwin. These packages contain native tools and libraries, so you can use the packaged components without compiling them. This guide explains how to choose a package, check compatibility, install it, and understand the scope of testing.

For instructions on building components from source, see Building the ML SDK for Vulkan®.

Package downloads and documentation

Use PyPI for Python wheels or GitHub releases for binary tarballs and ZIP files:

Component	Python wheels	Binary archives
Model Converter	PyPI	GitHub releases
VGF Library	PyPI	GitHub releases
Workload Library	PyPI	GitHub releases
Scenario Runner	PyPI	GitHub releases
Emulation Layer	PyPI	GitHub releases

Select the binary archive for your operating system and architecture from the release assets, then extract it and follow the component’s usage instructions. The platform and runtime requirements below still apply.

The SDK GitHub releases also provide a ZIP containing precompiled, versioned documentation. Download the documentation for the SDK release you are using and extract it to browse locally without building the documentation yourself.

Requirements for pip installation

Before installing a package with pip, ensure that your system has:

Python 3.10 or later.
A supported operating system and architecture. See Platforms.
A recent version of pip.

Python 3.10 or later is the general Python requirement. However, this does not mean that every package is available for every later Python version or platform. A compatible wheel must also have been published for your Python version, operating system, and architecture.

Supported platforms

The desktop platform support described in Platforms is summarized below. Check the files for your selected package release before installing; platform support does not guarantee that a wheel is available for every component or Python version.

Operating system	Architecture	Support notes
Linux	x86-64 and AArch64	All five components are supported. Check the wheel’s Linux compatibility tag and the runtime requirements below.
Windows®	x86-64	All five components are supported. Windows® on AArch64 is unsupported.
Darwin	Arm64	Model Converter and VGF Library are supported. Workload Library, Scenario Runner, and Emulation Layer support is experimental. Darwin on x86-64 is unsupported.

The current Linux binary packages are built and tested on AlmaLinux 8. Linux wheel builds target manylinux_2_28, with a minimum requirement of glibc 2.28 or later (glibc >= 2.28). You can use other compatible Linux distributions; AlmaLinux is not required on the installation system. The Python, architecture, and Vulkan® runtime requirements still apply. See the manylinux compatibility documentation.

For an older package release, check its wheel tags because the compatibility baseline can differ between releases.

Android™ AArch64 support is experimental and uses a separate native/APK workflow for runtime components. The desktop pip instructions on this page do not install Android™ packages. See Platforms and the component documentation for Android™ support and build instructions.

Create a virtual environment

Using a virtual environment is recommended:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip

On Windows®:

py -3 -m venv .venv
.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip

Check package availability

Before installing, open the package’s PyPI page and select Download files.

Check that the release contains a wheel compatible with:

Your operating system.
Your processor architecture.
Your Python version and ABI.

Wheel filenames include compatibility tags. For example, win_amd64 identifies Windows® x86-64, and aarch64 identifies Linux AArch64 in a Linux wheel tag. A cp310 interpreter tag identifies CPython 3.10; a py3-none wheel has no Python-version-specific ABI dependency, but can still contain native binaries and require a particular operating system. Linux and Darwin platform tags also encode an operating-system compatibility baseline. Let pip check these tags; renaming a wheel does not make it compatible with another system.

The Python requirement shown on the main PyPI page is not sufficient by itself. A compatible wheel must also appear on the Download files page.

The release compatibility matrix maps ML SDK for Vulkan® releases to coordinated component versions. It does not describe the availability of Python package files for particular platforms or Python versions.

Wheel availability can change between releases. For this reason, this page does not provide a fixed wheel availability table. pip selects a compatible wheel automatically when one is available.

Available packages

Install the components needed for your workflow:

Model Converter converts TOSA models into VGF artifacts.
VGF Library provides VGF file handling and the vgf_dump tool.
Workload Library provides a native library for applications that execute Vulkan® workloads.
Scenario Runner executes workloads described by scenario files.
Emulation Layer provides the Vulkan® ML emulation layers used when running workloads through emulation.

The commands below require binary wheels for the package and its dependencies. This avoids falling back to a source build when a compatible wheel is missing. See the pip installation options.

Component	Install command	Package description
Model Converter	`python -m pip install --only-binary=:all: ai-ml-sdk-model-converter`	Model Converter on PyPI
VGF Library	`python -m pip install --only-binary=:all: ai-ml-sdk-vgf-library`	VGF Library on PyPI
Workload Library	`python -m pip install --only-binary=:all: ai-ml-workload-library-for-vulkan`	Workload Library on PyPI
Scenario Runner	`python -m pip install --only-binary=:all: ai-ml-sdk-scenario-runner`	Scenario Runner on PyPI
Emulation Layer	`python -m pip install --only-binary=:all: ai-ml-emulation-layer-for-vulkan`	Emulation Layer on PyPI

If pip reports that no matching distribution is available, check the package’s Download files page. A wheel might not yet be available for your combination of Python version, operating system, and architecture. Check which package the error names: the missing wheel might belong to a dependency. Use a combination listed in the release’s available files, or follow Building the ML SDK for Vulkan® to build from source.

Vulkan® runtime requirements

The Model Converter and VGF Library do not execute Vulkan® workloads.

Running workloads with Scenario Runner or the Emulation Layer requires a Vulkan® 1.3 or later implementation. There is no separately documented minimum Vulkan® Loader version.

Linux

Use a Vulkan® 1.3-capable implementation with Mesa 23.x or later.

Windows®

The Windows® binary packages are built and tested on Windows® 11. Use a current Vulkan®-capable GPU driver when running workloads.

Use the Vulkan® Loader installed by the GPU driver’s Vulkan® Runtime. The LunarG Vulkan® SDK is not required when using prebuilt packages.

Darwin

Workload Library, Scenario Runner, and Emulation Layer support on Darwin is experimental.

Install the latest available LunarG Vulkan® SDK for Darwin. The SDK provides the Vulkan® Loader and a Vulkan® implementation through a translation layer.

See Using the ML SDK for Vulkan® on Darwin for driver selection, configuration, and current limitations.

Verify the installation

Check that the installed packages have consistent dependencies:

python -m pip check

You can also inspect an installed package:

python -m pip show ai-ml-sdk-model-converter
python -m pip show ai-ml-sdk-vgf-library
python -m pip show ai-ml-workload-library-for-vulkan
python -m pip show ai-ml-sdk-scenario-runner
python -m pip show ai-ml-emulation-layer-for-vulkan

These checks confirm installed package metadata and dependency consistency. To check execution, follow the component usage instructions below and run a conversion or scenario. Running a Vulkan® workload also checks the driver and layer configuration, which package installation alone does not validate.

Python versions and testing platforms

The current binary package build configuration targets CPython 3.10, 3.11, 3.12, 3.13, and 3.14 for VGF Library and Scenario Runner. Model Converter, Emulation Layer, and Workload Library use Python 3.10 to produce py3-none wheels, with Python 3.10 or later declared as their requirement. These are wheel build targets; check the selected release’s files for actual availability.

We test the pip packages for all five components on all platforms listed below, using Python 3.12 only.

Operating system	Architecture	Python used for testing
AlmaLinux 8	x86-64 and AArch64	3.12
Windows® 11	x86-64	3.12
Darwin 25.5.0	Arm64	3.12

Android™ AArch64 is also a testing target for native runtime components.

Testing on a platform does not establish support for every GPU, model, operator, or tensor format. Darwin runtime support and Android™ support remain experimental. See Platforms, Using the ML SDK for Vulkan® on Darwin, and each component’s documented limitations for your intended workload.