How to run Frigate on an old PC

Running Frigate on an old PC is a practical way to build a local-first camera setup. Frigate is an open-source network video recorder (NVR) with real-time AI object detection, and it keeps your footage on hardware you control instead of in someone else’s cloud. This guide covers realistic hardware, how Frigate actually installs, and the trade-offs to expect.

A quick clarification up front: Frigate is not a Home Assistant “custom component.” Frigate runs as its own service, either as a Home Assistant add-on (on Home Assistant OS or Supervised installs) or as a standalone Docker container. There is a separate Frigate integration (HACS custom component) that connects an already-running Frigate to Home Assistant for events, and a separate Lovelace card installed on top of that, but the NVR itself is a container.

Choose the Right Hardware

Frigate’s heaviest cost is object detection on the video stream. How you handle detection drives your hardware choice more than the CPU alone.

For a modest old PC, aim for:

• A 6th-gen Intel Core (Skylake, ~2015) or newer CPU. Intel chips matter here because their integrated GPU (iGPU) can do hardware video decoding and, on recent generations, OpenVINO-based detection.
• 8 GB of RAM (4 GB can work for a couple of cameras, but 8 GB gives you headroom).
• A wired Ethernet connection for reliable camera streams.
• Storage sized for your retention needs. Recordings add up fast at higher resolutions.

A small business-class mini PC is an excellent fit. The Lenovo ThinkCentre M-series (Tiny), the Intel NUC 12 Pro, the Minisforum UM790 Pro, or the Beelink EQ13 all run Frigate well, and the Intel-based ones can offload both decoding and detection to the iGPU.

On detection acceleration, note that guidance has shifted. A Google Coral TPU is still a low-power option, but Frigate’s current recommendation is that Coral is no longer the default starting point for new builds. A recent Intel iGPU running OpenVINO, or a discrete GPU, often outperforms it. Pick based on the hardware you already have.

A note on small boards and laptops: a Raspberry Pi can run Frigate for one or two low-resolution cameras, but it struggles to scale and benefits from a detection accelerator. The older NVIDIA Jetson Nano is not a great fit for current Frigate. A laptop like a MacBook Air M1 is not a good Frigate host, because Frigate’s hardware acceleration paths target Linux on x86 (Intel/AMD) or supported ARM SBCs, not Apple Silicon under macOS.

Set Up Your Environment

Frigate runs in a container, so you have two clean paths:

Path A — Home Assistant app. If you run Home Assistant OS on the machine, open Settings, Apps, then the App Store, add the Frigate repository, and install Frigate NVR. (Home Assistant 2026.2 renamed add-ons to apps. Same software, same Supervisor behind it — only the label and the menu changed, so older guides still say “Settings > Add-ons”.) This is the simplest route and keeps everything in one place, but it is the more constrained one for acceleration: apps run in a managed container, Nvidia GPUs are not supported at all, and reaching the Intel iGPU often means switching to the Full Access variant and turning off Protection mode.

Path B — Standalone Docker. Install a server Linux distribution (Debian or Ubuntu Server are good choices), install Docker, and run Frigate from a docker-compose.yml. This is the best-performing path because the container gets low-overhead access to the iGPU or a Coral device. You’ll map your camera config, a storage path for recordings, and any detector device (for example /dev/dri for an Intel iGPU, or /dev/bus/usb for a USB Coral).

Either way, your configuration lives in Frigate’s own config.yaml (not Home Assistant’s configuration.yaml). That file defines your cameras, their RTSP stream URLs, detection settings, and record/snapshot retention.

Connect Frigate to Your Smart Home

Home Assistant. After Frigate is running, install the Frigate integration (via HACS) and point it at Frigate’s URL. You get camera entities and motion and object sensors. The Frigate Lovelace card for clips and event review is a separate HACS install, not part of the integration. Frigate communicates with Home Assistant over MQTT, so you’ll have an MQTT broker (the Mosquitto add-on is the usual choice).

HomeKit. Frigate has no native HomeKit support. The practical route is to expose Frigate’s camera entities through Home Assistant’s built-in HomeKit Bridge integration, which surfaces them in the Apple Home app.

Hubitat. Hubitat has no direct Frigate driver. Most people bridge events through Home Assistant or use Hubitat’s MQTT support to react to Frigate’s MQTT messages. If Hubitat is your only hub, expect this to be the rough edge.

Optimize for Performance and Stability

To keep an older machine healthy:

• Use a substream for detection and a high-resolution stream only for recording. Detecting on a 720p substream dramatically cuts CPU load.
• Enable hardware acceleration for decoding (hwaccel_args) so the iGPU handles video, not the CPU.
• Tune detection zones and object filters so Frigate only processes the regions and objects you care about.
• Put recordings on a drive with enough endurance and capacity, and set sensible retention. A NAS such as a Synology or QNAP over a network share is a fine target for archived clips.

Skip the gimmicks: a smart plug power-cycling the PC is not a real reliability strategy and risks corrupting recordings or the filesystem. If Frigate misbehaves, fix the root cause, and let Docker (or the add-on supervisor) restart the container automatically with a restart policy.

Quick Verdict

An old Intel-based mini PC or desktop is a great Frigate host. Run Frigate as a Home Assistant add-on for simplicity, or as a standalone Docker container for best performance, lean on the Intel iGPU (or a Coral/GPU) for detection, detect on a substream, and keep recordings local. The result is capable, private video surveillance with no subscription and no cloud dependency.