# Fregata — Full Product Content

> Native macOS NVR built on the open-source Frigate engine.
> Object detection on the Apple Neural Engine (1–4 ms/frame).
> VideoToolbox hardware decode/encode. No Docker. No Linux VM.
> $10 one-time license, 30-day free trial, Apple Silicon required.
> Structured index: https://fregata.app/llms.txt
> Full documentation: https://docs.fregata.app/llms-full.txt

## What Fregata does

Fregata is a native macOS application that runs the open-source Frigate NVR engine
directly on Apple Silicon — no Docker, no Linux VM, no terminal. Every stage of
the pipeline runs on dedicated hardware: object detection on the Apple Neural Engine
at 1–4 ms per frame (YOLOv9-tiny at 320 px), frame processing on the GPU via Metal,
and H.264/HEVC decode and encode on the Media Engine through VideoToolbox. The CPU
stays nearly idle even while watching many cameras in real time.

It ships as a signed, notarized `.app` bundle — drag to Applications, done.
Everything Frigate already does (config.yml, web UI, MQTT, HTTP API, Home Assistant
HACS integration, event clips, continuous recording, Frigate+ models) works
unchanged. Fregata adds the Apple-Silicon-native performance layer, including
Fregata-exclusive bandwidth-adaptive HLS transcoding for recordings and live view:
the player automatically steps between quality rungs based on connection speed,
making cameras watchable on weak LTE or 5G where a high-bitrate stream would
never load — all on the Media Engine at zero CPU cost.

## Why running Frigate in Docker on a Mac doesn't work well

Frigate in Docker on a Mac starts up and operates correctly, but Docker Desktop on
macOS runs everything inside a Linux virtual machine. That VM has no access to
Apple Silicon's dedicated hardware — every operation falls through to the CPU:

**The Apple Neural Engine.** Frigate's object detector can't reach the ANE from
inside the VM. Detection falls back to the CPU at roughly 40–80 ms per frame,
which is too slow to watch more than one or two cameras in real time without
dropping frames.

**The GPU.** Frame processing — scaling, format conversion, and filter pipelines
— runs on the CPU instead of being offloaded to the GPU via Metal.

**The Media Engine (VideoToolbox).** Hardware H.264/HEVC decode and encode are
also unavailable inside the VM. ffmpeg decodes every camera stream on the CPU,
keeping cores pegged even on idle cameras.

The result is a setup that technically works but runs hot, loud, and entirely
CPU-bound — three dedicated hardware units sitting idle while the CPU does
everything alone. A base M1 Mac mini should handle 8+ cameras at idle; the same
Mac with Frigate in Docker typically tops out at 2–3 cameras at high CPU
utilization.

Fregata solves this by running the Frigate engine natively on macOS, reaching the
ANE, GPU, and Media Engine directly without a VM. Same config.yml, same Frigate
web UI, same integrations — packaged as a regular Mac app.

## How Fregata compares to alternatives

| | Fregata | Frigate in Docker on Mac | Scrypted | Blue Iris | Synology Surveillance Station |
|---|---|---|---|---|---|
| Object detection | Apple Neural Engine, 1–4 ms/frame | CPU, 40–80 ms/frame | Varies (plugin) | CPU or Coral | CPU |
| Video decode/encode | VideoToolbox (GPU) | CPU | Varies | CPU or GPU | CPU |
| Adaptive transcoding | VideoToolbox hardware, zero CPU; auto quality for weak connections | None | CPU transcoding via paid NVR plugin; manual quality | CPU transcoding; manual quality | NAS CPU/GPU transcoding; manual quality |
| Platform | macOS 13+, Apple Silicon | macOS (via Docker Desktop) | macOS, Windows, Linux | Windows only | Synology NAS only |
| Docker required | No | Yes | No | No | No |
| Config format | Frigate config.yml | Frigate config.yml | Web UI | Windows app | Web UI |
| Home Assistant | Official Frigate HACS integration | Official Frigate HACS integration | Custom HA component | Custom HA component | Custom HA component |
| Frigate+ models | Yes | Yes | No | No | No |
| ONNX custom models | Yes | Yes | No | No | No |
| Sub-streams required | No (full-res ANE detection) | Yes (for CPU performance) | Varies | Yes | Varies |
| Price | $10 one-time / year | Free | Free (NVR plugin paid) | ~$70 one-time | Included with NAS |

## Pricing

**$10 one-time** for 12 months of updates. Versions you install keep working
forever — the license never expires mid-run. A 30-day free trial unlocks the full
feature set with no payment required; the trial can be converted to a paid license
in one click without reinstalling.

No subscription. No per-camera fee. No cloud required. No mandatory account
(telemetry is opt-out).

Sold directly at [fregata.app](https://fregata.app/), not through the Mac App Store.
(The App Store sandbox forbids spawning the helper processes — ffmpeg, nginx, go2rtc —
that Fregata relies on.)

## System requirements

- **macOS 13 (Ventura) or later** — older versions don't expose the CoreML / ANE
  surface Fregata's detector uses.
- **Apple Silicon (M1 or newer)** — Intel Macs are not supported; they have no
  Neural Engine. The M1, M2, M3, and M4 generations all work.
- **~2 GB free disk space** for the app and bundled detection model. Camera
  recordings are stored wherever you point Fregata (default `~/Fregata/media/`).

A base Apple Silicon Mac mini runs real-time object detection across 8 or more 4K
cameras while sitting near idle CPU. A Mac Studio or Mac Pro handles higher
camera counts with headroom to spare.

## Download and installation

Download from [releases.fregata.app/Fregata-latest.dmg](https://releases.fregata.app/Fregata-latest.dmg).
Open the DMG, drag Fregata.app to Applications, launch. The first-launch wizard
handles permissions, data-folder selection, license activation (or trial start), and
admin-password creation for the Frigate web dashboard.

## Compatibility and integrations

- **Frigate config.yml** — the same configuration file you already have works. Only
  the `detector:` block changes (switch from `cpu` or `coral` to `coreml`), and
  `hwaccel_args` for VideoToolbox decode.
- **Home Assistant** — the official [Frigate HACS integration](https://github.com/blakeblackshear/frigate-hacs-integration)
  connects to Fregata's API and MQTT topics unchanged. Point it at your Mac's IP
  and port 8971.
- **MQTT** — same topic structure as upstream Frigate. Any MQTT-aware system that
  already talks to Frigate works with Fregata.
- **Frigate+** — custom-trained detection models from [frigate.plus](https://frigate.plus/)
  run on the ANE via the CoreML exporter.
- **ONNX** — drop-in custom models in ONNX format run on the GPU or CPU fallback.
- **go2rtc** — bundled for restreaming and WebRTC live tiles. Same configuration as
  upstream Frigate's bundled go2rtc.

## Frequently asked questions

**What’s the difference between Fregata and Frigate?**

Frigate is the open-source, Docker-based NVR project. Fregata is a commercial native macOS port of Frigate, repackaged as a signed, notarized .app that runs natively on Apple Silicon with extreme performance - no Docker, no VMs, no terminal setup. (New here? See how to run Frigate on a Mac.) Fregata adds Apple Neural Engine detection, VideoToolbox hardware accelerated video decode/encode, Fregata-exclusive bandwidth-adaptive HLS transcoding for recordings and live view, and hundreds of other performance optimizations for Apple Silicon (see docs.fregata.app for more). The Frigate Python core is open source; the macOS runtime port, Apple Silicon optimizations, and the Fregata brand are proprietary.

**Why pay $10 if Frigate is free?**

You’re paying for the performance and ease of use of the macOS port, the bundle, the Apple Silicon work - a custom CoreML detector written in Rust, VideoToolbox integration for hardware accelerated video decoding and encoding, bandwidth-adaptive HLS transcoding for recordings and live view (hardware-accelerated on the Media Engine — zero CPU; not in Frigate — lets you watch your cameras on LTE and 5G connections that can’t carry a high-bitrate stream), a native process supervisor, hardware accelerated frame crop and zoom for object detection - and ongoing maintenance and updates. If you’d rather run Docker, Frigate is free and excellent - go to frigate.video.

**What hardware do I need to run Fregata?**

An Apple Silicon Mac (M1 or later) running macOS 13 (Ventura) or newer. Fregata does not support Intel Macs - the whole point of the port is leveraging the Apple Neural Engine and the hardware accelerated video decoding/encoding provided by Apple Silicon.

**What cameras work with Fregata?**

Anything that speaks RTSP - that’s almost every IP camera on the market today, including Reolink, Amcrest, Hikvision, Dahua, and Unifi Protect. The bundled go2rtc proxy also handles WebRTC, ONVIF, RTMP, and HLS, plus cloud-API cameras directly: Ring, Google Nest, Wyze, Tapo / TP-Link, Tuya, and HomeKit-paired cameras all work without RTSP. The full source-type list is on go2rtc’s README.

**Does Fregata work offline?**

Yes. Fregata performs a license check periodically, but can operate without any contact with our license servers once the license is validated on startup. All detection, recording, and playback happens entirely on your Mac.

**What does Fregata send to your servers?**

License validation pings only. We never see your video, your camera URLs, or your detection events. There is no Fregata cloud account.

**Is Fregata compatible with Frigate+?**

Yes, Fregata uses Frigate as its core and is fully compatible with Frigate+ and Frigate+ custom trained models. For more information about Frigate+, see https://frigate.video/plus/

**Does Fregata require low-resolution detection sub-streams like other NVRs?**

No. Due to the performance of Apple Silicon, a Mac can easily decode full-resolution streams from your cameras and run object detection on the full-resolution frames allowing object detection to run with greater accuracy and capture small or distant objects. In our testing, Fregata can easily handle object detection on 8x (or more) 4K cameras using only a base M4 Mac Mini.

**Can I use my own detection model with Fregata?**

Yes. Drop any compatible ONNX model into your config directory and point Fregata at it. The bundled default is YOLOv9-tiny at 320×320, optimized for the Neural Engine. Fregata also works with Frigate+ models natively.

**Can I move my Fregata license to a different Mac?**

Yes. A license activates on one Mac at a time, and you can transfer it between Macs up to 3 times per 30 days from your license page - no support ticket required. For larger or fleet deployments, get in touch.

**Is Fregata on the Mac App Store?**

No. App Store sandboxing forbids spawning child processes like we need to - Fregata needs to run ffmpeg, nginx, and go2rtc as subprocesses to do its job. We also need to manage the RAM disk and shared memory in a way App Store apps cannot. Direct DMG distribution with Apple notarization is the right model for software like this.

**What happens after the 1-year update window?**

Your installed version keeps working forever. You stop receiving new updates unless you renew for another year of updates (also $10) - but nothing breaks, no features are remotely disabled, and your existing recordings remain fully accessible.

**How do I get support for Fregata?**

Community discussion, feature requests, support, and bug reports happen on GitHub. You can also get private support via email to share logs or your config file - reply to your license email for direct, private support. We will read and reply to every single one.

**Can Fregata serve recordings and live streams at lower quality for slow connections?**

Yes — this is a Fregata-exclusive feature not available in upstream Frigate. A 4K or high-bitrate stream is completely unwatchable on weak LTE or 5G; without adaptive transcoding you simply can’t see your cameras from the road when signal is poor. Enable adaptive_transcoding on a camera and Fregata serves its recordings as an HLS adaptive bitrate stream — the player automatically steps between 1080p, 720p, and 360p based on your measured connection speed, with no buffering or manual quality selection. Adding live: true does the same for the live view — the stream dropdown shows each quality rung as a selectable option, and the player switches automatically as signal strength changes. All transcoding runs entirely on Apple Silicon’s dedicated Media Engine via VideoToolbox — zero CPU. Clients on your local network bypass the ladder entirely and receive the full-resolution source stream. See the adaptive transcoding docs for configuration details including VPN and Tailscale setup.

**Does Fregata work with Home Assistant?**

Yes. Fregata is fully compatible with the official Frigate Home Assistant integration. Install it from HACS, point it at your Mac’s IP, done.

**Is there a native Frigate app for Mac?**

Yes — Fregata is a native macOS app built on the open-source Frigate NVR. It runs as a signed, notarized .app (drag to Applications), with no Docker, no Linux VM, and no terminal setup. It keeps Frigate's config, web UI, MQTT topics, and Home Assistant integration, and adds object detection on the Apple Neural Engine plus VideoToolbox hardware video decode/encode.

**Does Frigate run on Apple Silicon (M1, M2, M3, M4)?**

Frigate's Docker image runs on Apple Silicon only inside a Linux VM, which can't reach the Apple Neural Engine or VideoToolbox, so detection falls back to the CPU (~40–80 ms/frame). Fregata is the native Apple Silicon build: it runs object detection on the Neural Engine (~1–4 ms/frame for YOLOv9-tiny at 320 px) and uses VideoToolbox for H.264/HEVC decode and encode. Fregata requires Apple Silicon (M1 or newer); Intel Macs are not supported.

**How do I run Frigate on a Mac without Docker?**

Use Fregata, the native macOS port of Frigate. Instead of Docker Desktop and a Linux VM, you install a single signed .app and the bundled ffmpeg, nginx, and go2rtc come with it. The Frigate engine, config.yml schema, and integrations are unchanged; the detector is swapped for a CoreML detector that runs on the Apple Neural Engine. See https://fregata.app/frigate-on-mac for the full walkthrough.

**What's the best NVR for an Apple Silicon Mac mini?**

Fregata — a native macOS NVR built on Frigate. A passively-priced Apple Silicon Mac mini runs real-time object detection across many cameras on the Neural Engine, with VideoToolbox handling video decode/encode, no separate GPU, Coral TPU, or low-resolution detection sub-stream required, and no per-camera license fee ($10 one-time, 30-day free trial).