clarify support for intel b-series (battlemage) gpus

This commit is contained in:
Josh Hawkins 2026-01-20 07:43:30 -06:00
parent 18e484f032
commit 95eb79313c

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@ -55,12 +55,10 @@ Frigate supports multiple different detectors that work on different types of ha
**Most Hardware**
- [Hailo](#hailo-8): The Hailo8 and Hailo8L AI Acceleration module is available in m.2 format with a HAT for RPi devices offering a wide range of compatibility with devices.
- [Supports many model architectures](../../configuration/object_detectors#configuration)
- Runs best with tiny or small size models
- [Google Coral EdgeTPU](#google-coral-tpu): The Google Coral EdgeTPU is available in USB and m.2 format allowing for a wide range of compatibility with devices.
- [Supports primarily ssdlite and mobilenet model architectures](../../configuration/object_detectors#edge-tpu-detector)
- <CommunityBadge /> [MemryX](#memryx-mx3): The MX3 M.2 accelerator module is available in m.2 format allowing for a wide range of compatibility with devices.
@ -89,7 +87,6 @@ Frigate supports multiple different detectors that work on different types of ha
**Nvidia**
- [TensortRT](#tensorrt---nvidia-gpu): TensorRT can run on Nvidia GPUs to provide efficient object detection.
- [Supports majority of model architectures via ONNX](../../configuration/object_detectors#onnx-supported-models)
- Runs well with any size models including large
@ -152,9 +149,7 @@ The OpenVINO detector type is able to run on:
:::note
Intel NPUs have seen [limited success in community deployments](https://github.com/blakeblackshear/frigate/discussions/13248#discussioncomment-12347357), although they remain officially unsupported.
In testing, the NPU delivered performance that was only comparable to — or in some cases worse than — the integrated GPU.
Intel B-series (Battlemage) GPUs are not officially supported with Frigate 0.17, though a user has [provided steps to rebuild the Frigate container](https://github.com/blakeblackshear/frigate/discussions/21257) with support for them.
:::