---
# System prepended metadata

title: CUDA 13.2 on Jetson Orin (JetPack 6)

---

# CUDA 13.2 on Jetson Orin (JetPack 6)

## Problem

PyTorch nightly built for CUDA 13.2 (`cu132`) fails on Jetson Orin running JetPack 6.2.2,
because the bundled NVIDIA driver (540.5.0) only supports up to CUDA 12.6:

```
RuntimeError: The NVIDIA driver on your system is too old (found version 12060).
```

## System Info

| Component        | Version                        |
|------------------|--------------------------------|
| Board            | NVIDIA Jetson Orin             |
| JetPack          | 6.2.2 (L4T R36.5.0)           |
| Kernel           | 5.15.185-tegra                 |
| NVIDIA Driver    | 540.5.0                        |
| System CUDA      | 12.6                           |
| OS               | Ubuntu 22.04.5 LTS (aarch64)  |
| PyTorch          | 2.12.0.dev20260321+cu132       |
| Python           | 3.10.12                        |

## Solution: CUDA Forward Compatibility (cuda-compat-orin-13-2)

CUDA 13.2 introduced unified SBSA toolkit support for Jetson Orin. NVIDIA provides a
**CUDA Forward Compatibility** package (`cuda-compat-orin-13-2`) that supplies user-mode
CUDA 13.2 driver libraries that run on top of the existing JetPack 6 kernel driver.
No kernel driver update or JetPack reflash is required.

Reference: [CUDA 13.2 Blog Post](https://developer.nvidia.com/blog/cuda-13-2-introduces-enhanced-cuda-tile-support-and-new-python-features/)

## Installation Steps

### 1. Download the compatibility package

```bash
mkdir -p ~/cuda-compat-orin && cd ~/cuda-compat-orin

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/sbsa/cuda-compat-orin-13-2_13.2.44290101-1_arm64.deb \
     -O cuda-compat-orin-13-2.deb
```

### 2. Extract without root

No `sudo` required — just extract the `.deb` to a local directory:

```bash
dpkg-deb -x cuda-compat-orin-13-2.deb extracted/
```

The compat libraries will be at:

```
~/cuda-compat-orin/extracted/usr/local/cuda-13.2/compat_orin/
```

Key files:

```
libcuda.so -> libcuda.so.1 -> libcuda.so.1.1   (CUDA 13.2 user-mode driver)
libnvidia-ptxjitcompiler.so                      (PTX JIT compiler)
libnvidia-gpucomp.so                             (GPU compute library)
libnvidia-nvvm.so                                (NVVM compiler)
libcudadebugger.so.1                             (debugger support)
```

### 3. Set LD_LIBRARY_PATH

Prepend the compat library path so it takes priority over the system's CUDA 12.6 `libcuda.so`:

```bash
export LD_LIBRARY_PATH=/home/nvidia/cuda-compat-orin/extracted/usr/local/cuda-13.2/compat_orin${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}
```

### 4. Make it persistent (optional)

Add to `~/.bashrc`:

```bash
echo 'export LD_LIBRARY_PATH=/home/nvidia/cuda-compat-orin/extracted/usr/local/cuda-13.2/compat_orin${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}' >> ~/.bashrc
```

Or add to the venv activate script:

```bash
echo 'export LD_LIBRARY_PATH=/home/nvidia/cuda-compat-orin/extracted/usr/local/cuda-13.2/compat_orin${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}' >> ~/Projects/pytorch/.torch/bin/activate
```

## Verification

```bash
source ~/Projects/pytorch/.torch/bin/activate
python3
```

```python
import torch
print(torch.cuda.is_available())    # True
print(torch.cuda.get_device_name(0))  # Orin
x = torch.randn(3, 3, device='cuda')
print(x)                            # tensor([...], device='cuda:0')
```

## Known Warning: Compute Capability 8.7

```
UserWarning: Found GPU0 Orin which is of compute capability (CC) 8.7.
...
- 8.0 which supports hardware CC >=8.0,<9.0 except {8.7}
```

This PyTorch nightly was built with `sm_80` PTX but explicitly excludes CC 8.7 (Orin).
Kernels still run via **PTX JIT compilation** — functionally correct but with:

- One-time JIT compilation latency on first kernel launch
- Potentially suboptimal codegen (no Orin-specific tuning)

To fully resolve this, build PyTorch from source with:

```bash
export TORCH_CUDA_ARCH_LIST="8.7"
```

To suppress the warning at runtime:

```python
import warnings
warnings.filterwarnings("ignore", message=".*Found GPU.*compute capability.*")
```

## Alternative: Install system-wide with sudo

If you have root access, you can install the package properly:

```bash
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/sbsa/cuda-archive-keyring.gpg
sudo cp cuda-archive-keyring.gpg /usr/share/keyrings/

echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg arch=arm64] https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/sbsa/ /" \
  | sudo tee /etc/apt/sources.list.d/cuda-sbsa.list

sudo apt update
sudo apt install cuda-compat-orin-13-2
```

This installs to `/usr/local/cuda-13.2/compat_orin/` and may configure the library
path automatically.