Installing cuDNN Backend on Linux

Installing the CUDA Toolkit for Linux

Refer to the following instructions for installing CUDA on Linux, including the CUDA driver and toolkit: NVIDIA CUDA Installation Guide for Linux.

Installing Zlib

For Ubuntu users, to install the zlib package, run:

sudo apt-get install zlib1g

For RHEL users, to install the zlib package, run:

sudo yum install zlib

Installing the cuDNN Backend Packages on Linux

cuDNN can be installed using either distribution-specific packages (RPM and Debian packages), or a distribution-independent package (Tarballs).

The distribution-independent package has the advantage of working across a wider set of Linux distributions, but does not update the distribution’s native package management system. The distribution-specific packages interface with the distribution’s native package management system. It is recommended to use the distribution-specific packages, where possible.

Package Manager Installation

Installation using RPM or Debian packages interfaces with your system’s package management system. If the online network repository is enabled, RPM or Debian packages will be automatically downloaded at installation time using the package manager: apt-get or dnf. When using RPM or Debian local repo installers, the downloaded package contains a repository snapshot stored on the local filesystem in /var/. Such a package only informs the package manager where to find the actual installation packages, but will not install them.

Package Manager Network Installation

Ubuntu and Debian Network Installation

Enable the network repository. Perform the steps described in the NVIDIA CUDA Installation Guide for Ubuntu or the NVIDIA CUDA Installation Guide for Debian.

For the $distro/$arch noted in the above links, refer to the cuDNN Support Matrix for the $distro/$arch supported versions, as cuDNN’s Support Matrix might differ from CUDA.

Where $distro/$arch should be replaced by one of the following:
- ubuntu2204/x86_64
- ubuntu2204/sbsa
- ubuntu2204/cross-linux-sbsa
- ubuntu2204/arm64
- ubuntu2204/cross-linux-aarch64
- ubuntu2404/x86_64
- ubuntu2404/sbsa
- ubuntu2404/cross-linux-sbsa
- ubuntu2404/arm64
- ubuntu2404/cross-linux-aarch64
- ubuntu2604/x86_64
- ubuntu2604/sbsa
- debian12/x86_64
- debian12/sbsa
- debian12/cross-linux-sbsa
- debian13/x86_64
- debian13/sbsa
- debian13/cross-linux-sbsa
For arm64-sbsa repos:
- Native: $distro/sbsa
- Cross: $distro/cross-linux-sbsa
For aarch64-jetson repos:
- Native: $distro/arm64
- Cross: $distro/cross-linux-aarch64
Refresh the repository metadata.
```
sudo apt-get update
```
Install the per-CUDA meta-packages.

To install for CUDA 12, run:
```
sudo apt-get -y install cudnn9-cuda-12
```
To install for CUDA 13, run:
```
sudo apt-get -y install cudnn9-cuda-13
```
To install cuDNN JIT for CUDA 12, run:
```
sudo apt-get -y install cudnn9-jit-cuda-12
```
To install cuDNN JIT for CUDA 13, run:
```
sudo apt-get -y install cudnn9-jit-cuda-13
```

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.
cuDNN 9 JIT is supported only on x86_64 and SBSA (arm64-sbsa).
On supported platforms, the cudnn9-cross-sbsa and cudnn9-cross-aarch64 meta-packages install all the packages required for cross-platform development to SBSA (arm64-sbsa) and ARMv8 (aarch64-jetson), respectively.
- Cross arm64-sbsa for CUDA 12:
```
sudo apt-get -y install libcudnn9-cross-sbsa-cuda-12
```
- Cross arm64-sbsa for CUDA 13:
```
sudo apt-get -y install cudnn9-cross-sbsa
```
- Cross aarch64-jetson for CUDA 12:
```
sudo apt-get -y install libcudnn9-cross-aarch64-cuda-12
```
- Cross aarch64-jetson for CUDA 13:
```
sudo apt-get -y install cudnn9-cross-aarch64
```
On supported platforms, the cudnn9-jit-cross-sbsa meta-package installs all the packages required for cuDNN JIT cross-platform development to SBSA (arm64-sbsa).
- Cross arm64-sbsa for CUDA 12:
```
sudo apt-get -y install libcudnn9-jit-cross-sbsa-cuda-12
```
- Cross arm64-sbsa for CUDA 13:
```
sudo apt-get -y install cudnn9-jit-cross-sbsa
```

RHEL, Rocky, and Amazon Linux Network Installation

Enable the repository.
```
sudo dnf config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$distro/$arch/cuda-$distro.repo
sudo dnf clean all
```
Where $distro/$arch should be replaced by one of the following:
- rhel8/x86_64
- rhel8/sbsa
- rhel9/x86_64
- rhel9/sbsa
- rhel10/x86_64
- rhel10/sbsa
- amzn2023/x86_64
- amzn2023/aarch64

For Rocky users, only the following are supported.

For Rocky 8, rhel8/x86_64.
For Rocky 9, rhel9/x86_64.
For Rocky 10, rhel10/x86_64.

For Amazon Linux 2023, use $distro=amzn2023 and $arch of x86_64 or aarch64.

Install the per-CUDA meta-packages.

To install for CUDA 12, run:

sudo dnf -y install --allowerasing cudnn9-cuda-12

To install for CUDA 13, run:

sudo dnf -y install --allowerasing cudnn9-cuda-13

To install cuDNN JIT for CUDA 12, run:

sudo dnf -y install --allowerasing cudnn9-jit-cuda-12

To install cuDNN JIT for CUDA 13, run:

sudo dnf -y install --allowerasing cudnn9-jit-cuda-13

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.

SUSE Linux Enterprise Server and OpenSUSE Network Installation

Enable the repository.

sudo zypper addrepo https://developer.download.nvidia.com/compute/cuda/repos/$distro/$arch/cuda-$distro.repo
sudo zypper refresh

Where $distro/$ arch“ should be replaced by one of the following:

sles15/x86_64
opensuse15/x86_64

Install the per-CUDA meta-packages.

To install for CUDA 12, run:

sudo zypper -y install --allowerasing cudnn9-cuda-12

To install for CUDA 13, run:

sudo zypper -y install --allowerasing cudnn9-cuda-13

To install cuDNN JIT for CUDA 12, run:

sudo zypper -y install --allowerasing cudnn9-jit-cuda-12

To install cuDNN JIT for CUDA 13, run:

sudo zypper -y install --allowerasing cudnn9-jit-cuda-13

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.

Package Manager Local Installation

Ubuntu and Debian Local Installation

Before issuing the following commands, you must replace 9.x.y, $distro, and $architecture with your respective cuDNN version, OS distribution, and platform architecture.

Where $distro is one of the following:

ubuntu2204
ubuntu2404
ubuntu2604
debian12
debian13

And $architecture is one of the following:

For Ubuntu 26.04/24.04/22.04:
amd64
arm64
For Debian 13/12:
amd64
arm64

Debian 13 and Debian 12 are not supported on the ARMv8 (aarch64-jetson) platform.

Download the Debian package either from the developer website or through wget.
1. The local Debian package is available at https://developer.nvidia.com/cudnn. Click on the green buttons that describe your target platform and choose Deb (local) as the installer type.
2. Or, run:
```
wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-$distro-9.x.y_1.0-1_$architecture.deb
```

The following commands are specific to the SBSA (arm64-sbsa) and ARMv8 (aarch64-jetson) platforms.

Native arm64-sbsa:

wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-$distro-9.x.y_1.0-1_arm64.deb

Cross arm64-sbsa:

wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-cross-sbsa-$distro-9.x.y_1.0-1_all.deb

Native aarch64-jetson:

wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-tegra-repo-$distro-9.x.y_1.0-1_arm64.deb

Cross aarch64-jetson:

wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-cross-aarch64-$distro-9.x.y_1.0-1_all.deb

Navigate to your downloads directory containing the cuDNN Debian local installer file.

Enable the local repository.

sudo dpkg -i cudnn-local-repo-$distro-9.x.y_1.0-1_$architecture.deb

The following commands are specific to the SBSA (arm64-sbsa) and ARMv8 (aarch64-jetson) platforms.

Native arm64-sbsa:

sudo dpkg -i cudnn-local-repo-$distro-9.x.y_1.0-1_arm64.deb

Cross arm64-sbsa:

sudo dpkg -i cudnn-local-repo-cross-sbsa-$distro-9.x.y_1.0-1_all.deb

Native aarch64-jetson:

sudo dpkg -i cudnn-local-tegra-repo-$distro-9.x.y_1.0-1_arm64.deb

Cross aarch64-jetson:

sudo dpkg -i cudnn-local-repo-cross-aarch64-$distro-9.x.y_1.0-1_all.deb

Import the CUDA GPG key.

sudo cp /var/cudnn-local-*/cudnn-*-keyring.gpg /usr/share/keyrings/

Refresh the repository metadata.
```
sudo apt-get update
```
Install the per-CUDA meta-packages.

To install for CUDA 12, run:
```
sudo apt-get -y install cudnn9-cuda-12
```
To install for CUDA 13, run:
```
sudo apt-get -y install cudnn9-cuda-13
```
To install cuDNN JIT for CUDA 12, run:
```
sudo apt-get -y install cudnn9-jit-cuda-12
```
To install cuDNN JIT for CUDA 13, run:
```
sudo apt-get -y install cudnn9-jit-cuda-13
```

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.
cuDNN 9 JIT is supported only on x86_64 and SBSA (arm64-sbsa
The following commands are specific to the SBSA (arm64-sbsa) and ARMv8 (aarch64-jetson) platforms.
- Cross arm64-sbsa for CUDA 12:
```
sudo apt-get -y install libcudnn9-cross-sbsa-cuda-12
```
- Cross arm64-sbsa for CUDA 13:
```
sudo apt-get -y install cudnn9-cross-sbsa
```
- Cross arm64-jetson for CUDA 12:
```
sudo apt-get -y install libcudnn9-cross-aarch64-cuda-12
```
- Cross aarch64-jetson for CUDA 13:
```
sudo apt-get -y install cudnn9-cross-aarch64
```

The following commands are specific to cuDNN JIT on the SBSA (arm64-sbsa) platform.
- Cross arm64-sbsa for CUDA 12:
```
sudo apt-get -y install libcudnn9-jit-cross-sbsa-cuda-12
```
- Cross arm64-sbsa for CUDA 13:
```
sudo apt-get -y install cudnn9-jit-cross-sbsa
```

RHEL, Rocky, and Amazon Linux Local Installation

Before issuing the following commands, you must replace 9.x.y, $distro, and $architecture with your respective cuDNN version, OS distribution, and platform architecture.

Where $distro is one of the following:

For RHEL 10/Rocky 10:

rhel10
For RHEL 9/Rocky 9:
rhel9
For RHEL 8/Rocky 8:
rhel8
For Amazon Linux 2023:
amzn2023

And $architecture is one of the following:

For RHEL 10:
x86_64
aarch64
For Rocky 10:
x86_64
For RHEL 9:
x86_64
aarch64
For Rocky 9:
x86_64
For RHEL 8:
x86_64
aarch64
For Rocky 8:
x86_64
For Amazon Linux 2023:
x86_64
aarch64

Download the RPM package either from the developer website or through wget.
1. The local RPM package is available at https://developer.nvidia.com/cudnn. Click on the green buttons that describe your target platform and choose RPM (local) as the installer type.
2. Or, run:
```
wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-$distro-9.x.y-1.0-1.$architecture.rpm
```

For RHEL users, the following command is specific to the SBSA (arm64-sbsa) platform.

Native arm64-sbsa:

wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-$distro-9.x.y-1.0-1.aarch64.rpm

Navigate to your downloads directory containing the cuDNN RPM local installer file.

Enable the local repository.

sudo rpm -i cudnn-local-repo-$distro-9.x.y-1.0-1.$architecture.rpm

For RHEL users, the following command is specific to the SBSA (arm64-sbsa) platform.

Native arm64-sbsa:

sudo rpm -i cudnn-local-repo-$distro-9.x.y-1.0-1.aarch64.rpm

Refresh the repository metadata.
```
sudo dnf clean all
```

Install the per-CUDA meta-packages.

To install for CUDA 12, run:

sudo dnf -y install --allowerasing cudnn9-cuda-12

To install for CUDA 13, run:

sudo dnf -y install --allowerasing cudnn9-cuda-13

To install cuDNN JIT for CUDA 12, run:

sudo dnf -y install --allowerasing cudnn9-jit-cuda-12

To install cuDNN JIT for CUDA 13, run:

sudo dnf -y install --allowerasing cudnn9-jit-cuda-13

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.

SUSE Linux Enterprise Server and OpenSUSE Local Installation

Before issuing the following commands, you must replace 9.x.y, $distro, and $architecture with your respective cuDNN version, OS distribution, and platform architecture.

Where $distro is one of the following:

sles15
opensuse15

And $architecture is one of the following:

x86_64

Download the RPM package either from the developer website or through wget.
1. The local RPM package is available at https://developer.nvidia.com/cudnn. Click on the green buttons that describe your target platform and choose RPM (local) as the installer type.
2. Or, run:
```
wget https://developer.download.nvidia.com/compute/cudnn/9.x.y/local_installers/cudnn-local-repo-$distro-9.x.y-1.0-1.$architecture.rpm
```
Navigate to your downloads directory containing the cuDNN RPM local installer file.

Enable the local repository.

sudo rpm -i cudnn-local-repo-$distro-9.x.y-1.0-1.$architecture.rpm

Refresh the repository metadata.
```
sudo zypper refresh
```

Install the per-CUDA meta-packages.

To install for CUDA 12, run:

sudo zypper -y install --allowerasing cudnn9-cuda-12

To install for CUDA 13, run:

sudo zypper -y install --allowerasing cudnn9-cuda-13

To install cuDNN JIT for CUDA 12, run:

sudo zypper -y install --allowerasing cudnn9-jit-cuda-12

To install cuDNN JIT for CUDA 13, run:

sudo zypper -y install --allowerasing cudnn9-jit-cuda-13

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.

Additional Package Manager Capabilities

Meta-Packages

Meta-packages are RPM and Debian packages that contain no (or few) files but have multiple dependencies. They are used to install many cuDNN packages when you may not know the details of the packages you want.

Meta-Package Name	Intended Use Case
`cudnn`	Installs the latest available cuDNN for the latest available CUDA version.
`cudnn-jit`	Installs the latest available cuDNN JIT for the latest available CUDA version.
`cudnn9`	Installs the latest available cuDNN 9 for the latest available CUDA version.
`cudnn9-jit`	Installs the latest available cuDNN 9 JIT for the latest available CUDA version.
`cudnn-cuda-13`	Installs the latest available cuDNN for the latest available CUDA 13 version.
`cudnn9-cuda-13`	Installs the latest available cuDNN 9 for the latest available CUDA 13 version.
`cudnn9-jit-cuda-13`	Installs the latest available cuDNN 9 JIT for the latest available CUDA 13 version.
`cudnn-cuda-12`	Installs the latest available cuDNN for the latest available CUDA 12 version.
`cudnn9-cuda-12`	Installs the latest available cuDNN 9 for the latest available CUDA 12 version.
`cudnn9-jit-cuda-12`	Installs the latest available cuDNN 9 JIT for the latest available CUDA 12 version.
`cudnn-cross-sbsa`	Installs the latest available cuDNN for the latest available CUDA version meant for cross-platform development to SBSA.
`cudnn-jit-cross-sbsa`	Installs the latest available cuDNN JIT for the latest available CUDA version meant for cross-platform development to SBSA.
`cudnn9-cross-sbsa`	Installs the latest available cuDNN 9 for the latest available CUDA version meant for cross-platform development to SBSA.
`cudnn9-jit-cross-sbsa`	Installs the latest available cuDNN 9 JIT for the latest available CUDA version meant for cross-platform development to SBSA.
`cudnn-cross-aarch64`	Installs the latest available cuDNN for the latest available CUDA version meant for cross-platform development to ARMv8.
`cudnn9-cross-aarch64`	Installs the latest available cuDNN 9 for the latest available CUDA version meant for cross-platform development to ARMv8.

The above packages install the latest major and minor patch version of cuDNN 9.x. To install a specific cuDNN 9.x.y version, pin the cudnn9* package version to 9.x.y.

Base Packages

Base packages are RPM and Debian packages that contain actual cuDNN deliverables, such as binaries and headers. They can give you fine-grained control over what parts of cuDNN you want to install.

Base Package Name (Ubuntu/Debian)	Base Package Name (RHEL/Rocky)	Intended Use Case
`libcudnn9-cuda-13`	`libcudnn9-cuda-13`	Installs the runtime package which contains the latest available cuDNN 9 dynamic libraries for the latest available CUDA 13 version.
`libcudnn9-jit-cuda-13`	`libcudnn9-jit-cuda-13`	Installs the runtime package which contains the latest available cuDNN 9 JIT dynamic libraries for the latest available CUDA 13 version.
`libcudnn9-headers-cuda-13`	`libcudnn9-headers-cuda-13`	Installs the headers package which contains the latest available cuDNN 9 headers for the latest available CUDA 13 version.
`libcudnn9-dev-cuda-13`	`libcudnn9-devel-cuda-13`	Installs the dev package which contains the latest available cuDNN 9 dynamic library symlinks for the latest available CUDA 13 version. (The runtime and headers packages are dependencies.)
`libcudnn9-jit-dev-cuda-13`	`libcudnn9-jit-devel-cuda-13`	Installs the dev package which contains the latest available cuDNN 9 JIT dynamic library symlinks for the latest available CUDA 13 version. (The runtime and headers packages are dependencies.)
`libcudnn9-static-cuda-13`	`libcudnn9-static-cuda-13`	Installs the static package which contains the latest available cuDNN 9 static libraries for the latest available CUDA 13 version. (The dev and runtime packages are dependencies.)
`libcudnn9-cuda-12`	`libcudnn9-cuda-12`	Installs the runtime package which contains the latest available cuDNN 9 dynamic libraries for the latest available CUDA 12 version.
`libcudnn9-jit-cuda-12`	`libcudnn9-jit-cuda-12`	Installs the runtime package which contains the latest available cuDNN 9 JIT dynamic libraries for the latest available CUDA 12 version.
`libcudnn9-headers-cuda-12`	`libcudnn9-headers-cuda-12`	Installs the headers package which contains the latest available cuDNN 9 headers for the latest available CUDA 12 version.
`libcudnn9-dev-cuda-12`	`libcudnn9-devel-cuda-12`	Installs the dev package which contains the latest available cuDNN 9 dynamic library symlinks for the latest available CUDA 12 version. (The runtime and headers packages are dependencies.)
`libcudnn9-jit-dev-cuda-12`	`libcudnn9-jit-devel-cuda-12`	Installs the dev package which contains the latest available cuDNN 9 JIT dynamic library symlinks for the latest available CUDA 12 version. (The runtime and headers packages are dependencies.)
`libcudnn9-static-cuda-12`	`libcudnn9-static-cuda-12`	Installs the static package which contains the latest available cuDNN 9 static libraries for the latest available CUDA 12 version. (The dev and runtime packages are dependencies.)
`libcudnn9-samples`	`libcudnn9-samples`	Installs the latest available cuDNN samples source code.

The above packages install the latest major and minor patch version of cuDNN 9.x. To install a specific cuDNN 9.x.y version, pin the libcudnn9* package version to 9.x.y.

Tarball Installation

In an effort to meet the needs of a growing customer base requiring alternative installer packaging formats, as well as a means of input into community CI/CD systems, Tarballs are available for download.

Redist Archive

Tarballs are provided at https://developer.download.nvidia.com/compute/cudnn/redist/.

These .tar.xz archives do not replace existing packages such as .deb, .rpm, and are not meant for general consumption, as they are not installers.

For each release, a JSON manifest is provided such as redistrib_9.x.y.z.json, which corresponds to the cuDNN 9.x.y.z release label which includes the release date, the name of each component, license name, relative URL for each platform, and checksums.

Details on parsing these JSON files are described in Parsing Redistrib JSON.

Conda Installation

Starting with cuDNN 9.23.0, cuDNN and cuDNN JIT packages are published only on the conda-forge channel and are no longer published on the nvidia channel.

Before issuing the following commands, you must replace 9.x.y with your respective cuDNN version and <cuda-major-version> with your respective CUDA major version (12 or 13). Only x86_64 and arm64-sbsa Conda packages are available.

Installing cuDNN using Conda

To install cuDNN using Conda, run:

conda install cudnn cuda-version=<cuda-major-version> -c conda-forge

To install cuDNN JIT using Conda, run:

conda install cudnn-jit cuda-version=<cuda-major-version> -c conda-forge

Installing a Specific Release Version of cuDNN using Conda

To install a specific cuDNN release, pin the package version in the install command.

For example, for cuDNN:

conda install cudnn=9.x.y cuda-version=<cuda-major-version> -c conda-forge

For cuDNN JIT:

conda install cudnn-jit=9.x.y cuda-version=<cuda-major-version> -c conda-forge

Uninstalling cuDNN using Conda

To uninstall cuDNN using Conda, run:

conda remove cudnn

To uninstall cuDNN JIT using Conda, run:

conda remove cudnn-jit

Python Wheels - Linux Installation

NVIDIA provides Python Wheels for installing cuDNN through pip, primarily for the use of cuDNN with Python. With this installation method, the cuDNN installation environment is managed via pip. Additional care must be taken to set up your host environment to use cuDNN outside the pip environment.

Before issuing the following commands, you must replace 9.x.y.z with your respective cuDNN version. On Linux, only x86_64 and aarch64 (arm64-sbsa) architectures are supported.

Prerequisites

If your pip and wheel Python modules are not up-to-date, then use the following command to upgrade these Python modules. If these Python modules are out-of-date, then the commands which follow later in this section may fail.

python3 -m pip install --upgrade pip wheel

Installing cuDNN with Pip

To install cuDNN for CUDA 13, run:

python3 -m pip install nvidia-cudnn-cu13

To install cuDNN for CUDA 12, run:

python3 -m pip install nvidia-cudnn-cu12

To install cuDNN JIT for CUDA 13, run:

python3 -m pip install nvidia-cudnn-jit-cu13

To install cuDNN JIT for CUDA 12, run:

python3 -m pip install nvidia-cudnn-jit-cu12

To install cuDNN for a specific release version, include the release version in the command. For example, to install cuDNN 9.x.y.z for CUDA 13, run:

python3 -m pip install nvidia-cudnn-cu13==9.x.y.z

To install cuDNN 9.x.y.z for CUDA 12, run:

python3 -m pip install nvidia-cudnn-cu12==9.x.y.z

To install cuDNN 9.x.y.z JIT for CUDA 13, run:

python3 -m pip install nvidia-cudnn-jit-cu13==9.x.y.z

To install cuDNN 9.x.y.z JIT for CUDA 12, run:

python3 -m pip install nvidia-cudnn-jit-cu12==9.x.y.z

Only one CUDA toolkit version of cuDNN 9 can be installed at a time.

Verifying the Install on Linux

To verify that cuDNN is installed and is running properly, compile the mnistCUDNN sample located in the /usr/src/cudnn_samples_v9 directory in the Debian file.

Install the cuDNN samples.

sudo apt-get -y install libcudnn9-samples

sudo dnf -y install libcudnn9-samples

Go to the writable path.
```
cd $HOME/cudnn_samples_v9/mnistCUDNN
```
Compile the mnistCUDNN sample.
```
make clean && make
```
Run the mnistCUDNN sample.
```
./mnistCUDNN
```

If cuDNN is properly installed and running on your Linux system, you will see a message similar to the following:

Test passed!

Upgrading From Older Versions of cuDNN to cuDNN 9.x.y

To upgrade from an older cuDNN version to 9, refer to the Package Manager Installation section and follow the steps for your target platform.

Starting with cuDNN Backend 9.10.0, side-by-side installation with previous versions of cuDNN Backend is no longer supported. If a previous version of cuDNN Backend is installed on your system, the package manager handles the uninstallation of the previous version as follows:

The Debian package manager automatically uninstalls the previous version.
The RPM package manager prompts you to pass a flag to uninstall the previous version.