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Update hardware docs to point to NPU support and highlight supported models

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Nicolas Mowen 2025-10-16 12:39:02 -06:00
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31
docs/docs/configuration/object_detectors.md
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@ -253,11 +253,11 @@ Hailo8 supports all models in the Hailo Model Zoo that include HailoRT post-proc
## OpenVINO Detector
The OpenVINO detector type runs an OpenVINO IR model on AMD and Intel CPUs, Intel GPUs and Intel VPU hardware. To configure an OpenVINO detector, set the `"type"` attribute to `"openvino"`.
The OpenVINO detector type runs an OpenVINO IR model on AMD and Intel CPUs, Intel GPUs and Intel NPUs. To configure an OpenVINO detector, set the `"type"` attribute to `"openvino"`.
The OpenVINO device to be used is specified using the `"device"` attribute according to the naming conventions in the [Device Documentation](https://docs.openvino.ai/2024/openvino-workflow/running-inference/inference-devices-and-modes.html). The most common devices are `CPU` and `GPU`. Currently, there is a known issue with using `AUTO`. For backwards compatibility, Frigate will attempt to use `GPU` if `AUTO` is set in your configuration.
The OpenVINO device to be used is specified using the `"device"` attribute according to the naming conventions in the [Device Documentation](https://docs.openvino.ai/2025/openvino-workflow/running-inference/inference-devices-and-modes.html). The most common devices are `CPU`, `GPU`, or `NPU`.
OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will also run on AMD CPUs despite having no official support for it. A supported Intel platform is required to use the `GPU` device with OpenVINO. For detailed system requirements, see [OpenVINO System Requirements](https://docs.openvino.ai/2024/about-openvino/release-notes-openvino/system-requirements.html)
OpenVINO is supported on 6th Gen Intel platforms (Skylake) and newer. It will also run on AMD CPUs despite having no official support for it. A supported Intel platform is required to use the `GPU` or `NPU` device with OpenVINO. For detailed system requirements, see [OpenVINO System Requirements](https://docs.openvino.ai/2025/about-openvino/release-notes-openvino/system-requirements.html)
:::tip
@ -267,16 +267,25 @@ When using many cameras one detector may not be enough to keep up. Multiple dete
detectors:
ov_0:
type: openvino
device: GPU
device: GPU # or NPU
ov_1:
type: openvino
device: GPU
device: GPU # or NPU
```
:::
### OpenVINO Supported Models
| Model | GPU | NPU | Notes |
| ------------------------------------- | --- | --- | ------------------------------------------------------------ |
| [YOLOv9](#yolo-v3-v4-v7-v9) | ✅ | ✅ | Recommended for GPU & NPU |
| [RF-DETR](#rf-detr) | ✅ | | |
| [YOLO-NAS](#yolo-nas) | ✅ | ❌ | YOLO-NAS only works on NPU in non-flat format |
| [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models |
| [YOLOX](#yolox) | ✅ | | |
| [D-FINE](#d-fine) | ❌ | ❌ | |
#### SSDLite MobileNet v2
An OpenVINO model is provided in the container at `/openvino-model/ssdlite_mobilenet_v2.xml` and is used by this detector type by default. The model comes from Intel's Open Model Zoo [SSDLite MobileNet V2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/ssdlite_mobilenet_v2) and is converted to an FP16 precision IR model.
@ -287,7 +296,7 @@ Use the model configuration shown below when using the OpenVINO detector with th
detectors:
ov:
type: openvino
device: GPU
device: GPU # Or NPU
model:
width: 300
@ -348,7 +357,7 @@ After placing the downloaded onnx model in your config folder, you can use the f
detectors:
ov:
type: openvino
device: GPU
device: GPU # or NPU
model:
model_type: yolo-generic
@ -609,6 +618,14 @@ detectors:
### ONNX Supported Models
| Model | Nvidia GPU | AMD GPU | Notes |
| ------------------------------------- | ---------- | ------- | ------------------------------------------------------------ |
| [YOLOv9](#yolo-v3-v4-v7-v9-2) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [RF-DETR](#rf-detr) | ✅ | ❌ | Supports CUDA Graphs for optimal Nvidia performance |
| [YOLO-NAS](#yolo-nas-1) | ⚠️ | ⚠️ | Not supported by CUDA Graphs |
| [YOLOX](#yolox-1) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [D-FINE](#d-fine) | ⚠️ | ❌ | Not supported by CUDA Graphs |
There is no default model provided, the following formats are supported:
#### YOLO-NAS

3
docs/docs/frigate/hardware.md
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@ -78,7 +78,7 @@ Frigate supports multiple different detectors that work on different types of ha
**Intel**
- [OpenVino](#openvino---intel): OpenVino can run on Intel Arc GPUs, Intel integrated GPUs, and Intel CPUs to provide efficient object detection.
- [OpenVino](#openvino---intel): OpenVino can run on Intel Arc GPUs, Intel integrated GPUs, and Intel NPUs to provide efficient object detection.
- [Supports majority of model architectures](../../configuration/object_detectors#openvino-supported-models)
- Runs best with tiny, small, or medium models
@ -142,6 +142,7 @@ The OpenVINO detector type is able to run on:
- 6th Gen Intel Platforms and newer that have an iGPU
- x86 hosts with an Intel Arc GPU
- Intel NPUs
- Most modern AMD CPUs (though this is officially not supported by Intel)
- x86 & Arm64 hosts via CPU (generally not recommended)