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Installing TensorRT-RTX#

TensorRT-RTX can be installed from an SDK zip file on Windows or a tarball on Linux. Before proceeding, ensure you have met all Prerequisites.

Windows SDK Installation#

  1. Decompress the Windows zip package to extract the following:

    • Core library and ONNX parser DLLs and import libraries

    • Development headers

    • Source code samples

    • Documentation

    • Python bindings

    • The tensorrt_rtx executable for building engines and running inference from the command line

    • Licensing information and open-source acknowledgments

    Note

    The DLLs are signed and verified with the signtool utility. Remember to add the directories containing the DLLs and executable files to your PATH environment variable.

  2. Optionally, install the Python bindings.

    $version = "1.4.0.0" # Replace with newest version
$arch = "amd64" # Replace with your architecture
$pyversion = "311" # For Python 3.11, replace with your
                   # Python version
$wheel = "TensorRT-RTX-$version\tensorrt_rtx-$version-cp$pyversion-none-win_$arch.whl"
python3 -m pip install $wheel

Linux Tarball Installation#

TensorRT-RTX can be installed from a tarball package on Linux. For supported distributions and CUDA requirements, refer to the Prerequisites page.

  1. Download the repo file that matches your operating system version and CPU architecture.

  2. Unzip the tarball, optionally adding the path of the executable to your PATH variable and the path of the library to your LD_LIBRARY_PATH variable.

    version = "1.4.0.0" # Replace with newest version
arch = "x86_64"      # Replace with your architecture
cuda = "12.9"        # Replace with your CUDA version
tarfile = "TensorRT-RTX-${version}.Linux.${arch}-gnu-${cuda}.tar.gz"
tar -xzf $tarfile
export PATH=$PATH:$PWD/TensorRT-RTX-${version}/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$PWD/TensorRT-RTX-${version}/lib

  3. Optionally, install the Python bindings.

    pyversion = "311" # Assuming Python 3.11, else replace with your
                  # Python version
wheel = "tensorrt_rtx-${version}-cp${pyversion}-none-linux_${arch}.whl"
python3 -m pip install TensorRT-RTX-${version}/python/${wheel}

Next Steps#

After installation, verify your setup and deploy your first model: