Use this page when you need the NVIDIA cuVS Python package.

All NVIDIA cuVS routine implementations live in the C++ core. The Python bindings call into the native C and C++ libraries, so environments that use shared libraries need both libcuvs_c and libcuvs installed. The pip wheels bundle these native libraries for Python use.

Install Pre-Compiled Packages

Install the Python package with conda:

$
# CUDA 13
$
conda install -c rapidsai -c conda-forge cuvs cuda-version=13.3
$
$
# CUDA 12
$
conda install -c rapidsai -c conda-forge cuvs cuda-version=12.9

You can also install through pip:

$
# CUDA 13
$
pip install cuvs-cu13
$
$
# CUDA 12
$
pip install cuvs-cu12

The pip packages statically link the C and C++ libraries, so libcuvs and libcuvs_c shared libraries are not readily available for use by external code.

Build From Source

Before building from source, review the shared C++ source-build prerequisites, including the recommended conda environment setup for build dependencies.

Build and install the Python package with:

$
./build.sh python

Uninstall the Python package with:

$
./build.sh python --uninstall

If the Python changes depend on native C or C++ changes, rebuild the native libraries first:

$
./build.sh libcuvs python