onnxruntime/docs/tutorials/csharp/csharp-gpu.md

---
title: Configure CUDA for GPU with C#
description: Configure CUDA and cuDNN for ONNX Runtime with C# on Windows 11
parent: Inference with C#
grand_parent: Tutorials
has_children: false
nav_order: 1
---

# Configure CUDA and cuDNN for GPU with ONNX Runtime and C# on Windows 11

{: .no_toc }

## Prerequisites
- Windows 11
- Visual Studio 2019 or 2022
 
## Steps to Configure CUDA and cuDNN for ONNX Runtime with C# on Windows 11

- [Download and install the CUDA toolkit](https://developer.nvidia.com/cuda-toolkit-archive) based on the supported version for the ONNX Runtime Version.

- [Download and install the cuDNN version](https://developer.nvidia.com/rdp/cudnn-archive) based on the supported version for the ONNX Runtime Version.

See this table for supported versions:

| ONNX Runtime Version | CUDA Toolkit Version | cuDNN Version|
|----------------------|----------------------|--------------|
| 1.13 - 1.16          | 11.6                 | 8.5.0.96     |
| 1.9 - 1.12           | 11.4                 | 8.2.2.26     |

NOTE: Full table can be found [here](https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements)


- Follow section [2. Installing cuDNN on Windows](https://docs.nvidia.com/deeplearning/cudnn/installation/windows.html). NOTE: Skip step 5 in section 2.3 on updating Visual Studio settings, this is only for C++ projects.

- Restart your computer and verify the installation by running the following command or in python with PyTorch:

```bash
nvcc --version
```

```python
import torch
torch.cuda.is_available()
```

- Now you can enable GPU in the C# ONNX Runtime API with the following code:

```cs
// keep in mind almost all of the classes are disposable.
using var gpuSessionOptions = SessionOptions.MakeSessionOptionWithCudaProvider(0);
using var session = new InferenceSession(modelPath, gpuSessionOptions);
```

## Checkout more C# ONNX Runtime resources
- [C# API Doc](https://onnxruntime.ai/docs/api/csharp/api)
- [Get Started with C# in ONNX Runtime](https://onnxruntime.ai/docs/get-started/with-csharp.html)