> For the complete documentation index, see [llms.txt](https://docs.degirum.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.degirum.com/pysdk/runtimes-and-drivers/tensorrt.md).

# TensorRT

PySDK supports the NVIDIA TensorRT runtime on Linux, Windows, and NVIDIA Jetson hardware. This page walks through installation on each platform.

## Supported Versions

PySDK is validated with the following setups:

1. AMD64 host, CUDA GPU compute capability 8.9, CUDA 12.4, TensorRT 10.6.
2. AMD64 host, CUDA GPU compute capability 12.0, CUDA 12.9, TensorRT 10.13.
3. ARM64 host, JetPack 6.2.

{% hint style="info" %}
CUDA GPU compute capability is determined by the [GPU installed in the system](https://developer.nvidia.com/cuda-gpus). Each level of CUDA GPU compute capability requires a minimum CUDA version (see the "Max CC" column in [this compatibility table](https://stackoverflow.com/questions/28932864/which-compute-capability-is-supported-by-which-cuda-versions/28933055#28933055)). In practice, RTX 5000 series GPUs require CUDA versions greater than 12.6 and a matching TensorRT version.
{% endhint %}

## Linux Installation

### CUDA

We recommend the local Debian Installer method.

{% stepper %}
{% step %}
Make sure you have a compatible GPU and that its drivers are installed.
{% endstep %}

{% step %}
Download CUDA from the [NVIDIA CUDA Toolkit archive](https://developer.nvidia.com/cuda-toolkit-archive).
{% endstep %}

{% step %}
Follow NVIDIA's [CUDA installation guide for Ubuntu](https://docs.nvidia.com/cuda/cuda-quick-start-guide/index.html#ubuntu).
{% endstep %}

{% step %}
Update `PATH` and `LD_LIBRARY_PATH`, replacing `<VERSION>` with the version you installed:

{% code overflow="wrap" %}

```bash
export PATH=/usr/local/cuda-<VERSION>/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-<VERSION>/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
```

{% endcode %}
{% endstep %}

{% step %}
Verify the installation:

{% code overflow="wrap" %}

```bash
nvcc --version
```

{% endcode %}
{% endstep %}
{% endstepper %}

As an alternative, the default system repository often includes a supported version of CUDA.

### TensorRT

We recommend the local Debian Installer method.

{% stepper %}
{% step %}
Follow NVIDIA's [TensorRT download and installation instructions](https://docs.nvidia.com/deeplearning/tensorrt/latest/installing-tensorrt/installing.html#downloading-tensorrt).
{% endstep %}

{% step %}
Install the full `tensorrt` package. cuDNN is not required.
{% endstep %}

{% step %}
The `.deb` installer handles `LD_LIBRARY_PATH` automatically.
{% endstep %}
{% endstepper %}

## Windows Installation

### CUDA

Follow NVIDIA's [CUDA installation guide for Windows](https://docs.nvidia.com/cuda/cuda-quick-start-guide/index.html#windows). Python wheels are not required.

### TensorRT

{% stepper %}
{% step %}
Follow steps 1–4 of NVIDIA's [TensorRT zip-file installation guide](https://docs.nvidia.com/deeplearning/tensorrt/latest/installing-tensorrt/installing.html#zip-file-installation).
{% endstep %}

{% step %}
On Windows, TensorRT does not update `PATH` automatically. Make sure you complete step 4 from the guide above.
{% endstep %}
{% endstepper %}

## JetPack Installation

CUDA and TensorRT are included in JetPack. PySDK supports JetPack 6.2. See NVIDIA's [JetPack installation guide](https://docs.nvidia.com/sdk-manager/install-with-sdkm-jetson/index.html) for details.