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5 changes: 3 additions & 2 deletions docs/docs/features/ml-hardware-acceleration.md
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Expand Up @@ -11,7 +11,7 @@ You do not need to redo any machine learning jobs after enabling hardware accele

- ARM NN (Mali)
- CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher)
- OpenVINO (Intel discrete GPUs such as Iris Xe and Arc)
- OpenVINO (Intel GPUs such as Iris Xe and Arc)

## Limitations

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#### OpenVINO

- The server must have a discrete GPU, i.e. Iris Xe or Arc. Expect issues when attempting to use integrated graphics.
- Integrated GPUs are more likely to experience issues than discrete GPUs, especially for older processors or servers with low RAM.
- Ensure the server's kernel version is new enough to use the device for hardware accceleration.
- Expect higher RAM usage when using OpenVINO compared to CPU processing.

## Setup

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