Installing cuDNN on Windows


For the latest compatibility software versions of the OS, CUDA, the CUDA driver, and the NVIDIA hardware, refer to the cuDNN Support Matrix.

Installing NVIDIA Graphic Drivers

Install up-to-date NVIDIA graphics drivers on your Windows system.

  1. Go to: NVIDIA drivers.

  2. Select the GPU and OS version from the drop-down menus.

  3. Download and install the NVIDIA driver as indicated on that web page. For more information, select the ADDITIONAL INFORMATION tab for step-by-step instructions on installing a driver.

  4. Restart your system to ensure that the graphics driver takes effect.

Installing the CUDA Toolkit for Windows

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

Downloading cuDNN for Windows

cuDNN is available at Click on the green buttons that describe your target platform and choose one of the following installer formats:

  • Graphical Installation (executable) - the graphical installer bundles the available per-CUDA cuDNN versions in one package, where the desired CUDA version can be selected at install time through the graphical user interface.

  • Tarball Installation (zip) - per-CUDA cuDNN versions are provided as separate tarballs (zip) at These .zip archives do not replace the graphical installer 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.

Installing on Windows

The following steps describe how to build a cuDNN dependent program. You must replace 9.x and 9.x.y.z with your specific cuDNN version.

Graphical Installation

Install cuDNN by executing the cuDNN installer and following the on-screen prompts.

Tarball Installation

In the following steps, the package directory path is referred to as <packagepath>.

  1. Navigate to your <packagepath> directory containing the cuDNN package.

  2. Unzip the cuDNN package.

  3. Copy the following files from the unzipped package into the NVIDIA cuDNN directory.

    1. Copy bin\cudnn*.dll to C:\Program Files\NVIDIA\CUDNN\v9.x\bin.

    2. Copy include\cudnn*.h to C:\Program Files\NVIDIA\CUDNN\v9.x\include.

    3. Copy lib\x64\cudnn*.lib to C:\Program Files\NVIDIA\CUDNN\v9.x\lib.

  4. Set the following environment variable to point to where cuDNN is located. To access the value of the $(PATH) environment variable, perform the following steps:

    1. Open a command prompt from the Start menu.

    2. Type Run and hit Enter.

    3. Issue the control sysdm.cpl command.

    4. Select the Advanced tab at the top of the window.

    5. Click Environment Variables at the bottom of the window.

    6. Add the NVIDIA cuDNN bin directory path to the PATH variable:

      Variable Name: PATH
      Value to Add: C:\Program Files\NVIDIA\CUDNN\v9.x\bin
  5. Add cuDNN to your Visual Studio project.

    1. Open the Visual Studio project, right-click on the project name in Solution Explorer, and choose Properties.

    2. Click VC++ Directories and append C:\Program Files\NVIDIA\CUDNN\v9.x\include to the Include Directories field.

    3. Click Linker > General and append C:\Program Files\NVIDIA\CUDNN\v9.x\lib\x64 to the Additional Library Directories field.

    4. Click Linker > Input and append cudnn.lib to the Additional Dependencies field and click OK.

Upgrading cuDNN

Navigate to the directory containing cuDNN and delete the old cuDNN bin, lib, and header files. Remove the path to the directory containing cuDNN from the $(PATH) environment variable. Reinstall a newer cuDNN version by following the steps in Installing cuDNN On Windows.

Python Wheels - Windows 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 Windows, only the x86_64 architecture is supported.


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.

py -m pip install --upgrade pip wheel

Installing cuDNN with Pip

To install cuDNN for CUDA 11, run:

py -m pip install nvidia-cudnn-cu11

To install cuDNN for CUDA 12, run:

py -m pip install nvidia-cudnn-cu12

To install cuDNN for a specific release version, include the release version in the command. For example, to install for CUDA 11, run:

py -m pip install nvidia-cudnn-cu11==9.x.y.z

To install for CUDA 12, run:

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


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