# NVIDIA® GPU Requirements

The following information covers the requirements when utilizing an NVIDIA GPU with your VisionPro Deep Learning application. The GPU is utilized by Deep Learning during the development of your application, typically with the training of tools. In addition, a GPU can also be used during runtime deployment, where it increases performance of runtime workspaces.

## NVIDIA Driver Support

- GeForce® RTX driver greater than or equal to 461.09

- NVIDIA RTX / Quadro® / Data Center driver greater than or equal to R460 U2 (461.09) (Optimal Driver for Enterprise).

  - It is highly recommended to visit https://www.nvidia.com/Download/Find.aspx to find the right versions for your GPU as your GPU may require higher version than R460 U2 (461.09).

  Note: For more information about supported drivers, please visit the Cognex Support Site.

## Supported NVIDIA GPUs

VisionPro Deep Learning 2.0 aims to support the most common GPU families, but it’s not practical to test every model or driver. The table below indicates those models we have explicitly tested and confirmed work, as well as those few models and families that do not work. Most other common NVIDIA GPUs other than very new models have been used successfully by customers, even if they haven’t been explicitly tested. In addition, we share specifications for minimum GPU capability, as well as recommendations high performance GPUs for demanding applications, such as those using the new High Detail mode of the Green Classify Tool.

- Minimum recommended performance: GTX 1060 6GB
- Recommended for high performance: GTX 1080 Ti / RTX 2080 Ti / RTX 3080

GPU | Model | Tested by Cognex | Recommended for High Performance
--- | --- | --- | ---
NVIDIA GeForce® | GTX 1060 6GB | Tested |
GTX 1070 |  |
GTX 1080 | Tested |
GTX 1080 Ti | Tested | Recommended
RTX™ 2070 |  |
RTX 2080 |  |
RTX 2080 Ti | Tested | Recommended
RTX 3060 |  |
RTX 3060 Ti |  |
RTX 3070 | Tested |
RTX 3080 | Tested | Recommended
RTX 3090 | Tested | Recommended
NVIDIA RTX / Quadro® | P2000 |  |
P4000 | Tested |
P5000 |  | Recommended
GV100* |  | Recommended
RTX 4000 |  |
RTX 5000 |  | Recommended
RTX 6000 |  | Recommended
RTX 8000 |  | Recommended
Titan V* |  | Recommended
Titan RTX |  | Recommended
NVIDIA Tesla® | V100* |  |
Models known not to work: GTX 1660 and GTX 1650: Please note that low performance and slow training time with unknown reason.
Note: When selecting a GPU, Cognex only supports NVIDIA GPUs. VisionPro Deep Learning 2.0 supports the use of any NVIDIA CUDA® enabled GPU that provides a compute capability of 3.0 and higher, and requires a driver version greater than or equal to 461.09. CUDA compute capability 3.0 or higher is required to use the core VisionPro Deep Learning functionality. The Low Precision parameter requires CUDA compute capability 6.1 or higher (for more information, visit the NVIDIA website). When training and processing High Detail mode, a requirement of 8 GB of GPU memory is for runtime operation, and 10 GB of GPU memory is recommended for training. The NVIDIA GeForce Titan V, NVIDIA RTX / Quadro® GV100 and Tesla V100 include NVIDIA Tensor Cores. VisionPro Deep Learning 2.0 will automatically utilize Tensor Cores if they are present, provided you have a Standard or Advanced security license. Please contact your Cognex Sales Representative for information about enabling the functionality on your Cognex Security Dongle.