Inspect detector inference time and skipped processing during a real motion burst. Change model/detector capacity before assuming additional RAM will accelerate inference.
Busy camera zones and multiple active views.Hardwarevereisten voor Frigate: RAM, CPU, opslag, cameradetectie en bewaartermijn
Plan de RAM, CPU-instructies, videodecodering, objectdetectie en opslag voor opnamen voor Frigate, met aanbevelingen voor ZimaOS en Zima-hardware op basis van de werklast.
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Frigate hardware requirements at a glance
Frigate publishes a 4 GB basic RAM baseline, an 8 GB minimum for enrichments and a 16 GB recommendation. It also requires AVX and AVX2. Camera activity, decoding, detection models and recording retention must be sized separately.
- RAM
- Official planning guidance: 4 GB for a very basic setup with a dedicated detector and no enrichments; 8 GB minimum with enrichments; 16 GB recommended for more cameras or substantial enrichments.
- CPU
- AVX and AVX2 are required. Core count alone does not establish camera capacity: decoding, motion and simultaneous detections determine practical CPU pressure.
- Storage
- Plan recording bitrate × retention separately from the config/database and model cache. At continuous recording, 1 Mb/s is about 10.8 GB/day before filesystem overhead.
- Video decoding
- Pass through the supported integrated/discrete GPU and configure the matching FFmpeg preset. Intel iGPU decoding and object detection are separate workloads.
- Object detection
- Select an appropriate detector and model. Intel OpenVINO is an option; a discrete GPU is not a universal requirement, and a Coral is no longer the default recommendation for new installations.
- Best Zima starting point
- ZimaBoard 2 832 can suit a small, tuned workload with Intel acceleration and separate recording storage. Choose 1664 for memory headroom or ZimaCube 2 for capacity and stronger mixed processing.
From official requirements to the right setup
Plan the complete Frigate workload before selecting a server.
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Official requirements
Apply the official RAM tiers and AVX/AVX2 instruction-set requirement before counting cameras. Use the image and device configuration appropriate to your selected stable Frigate release.
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Confirm your needs
Record each stream bitrate, codec, detection resolution/FPS and likely simultaneous motion. Size video decoding separately from detector inference; lower-resolution detection substreams can reduce processing without reducing recording resolution.
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Leave room to grow
Persist /config and /media/frigate on suitable storage. Include database, model cache, clips and continuous recordings. Calculate continuous capacity from measured bitrates, retention days and headroom rather than advertised camera resolution alone.
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Run it on ZimaOS
Open the confirmed Frigate ZimaOS App Store page, then review storage, shared memory and accelerator access before relying on the installation. Validate the selected detector and FFmpeg hardware acceleration on the actual host.
Check every playback client
- Camera codecs and stream bitrates
- Detection resolution and FPS
- Simultaneous motion activity
- Detector backend and model
- AVX/AVX2 and GPU device access
- Shared-memory sizing for streams
- Continuous/event retention days
- Recording disk throughput and capacity
Official minimum requirements
Checked on October 23, 2026 against official documentation and the project repository. Latest stable release observed: v0.18.2 (upstream); the verified ZimaOS catalog entry advertises an older release, so check the installed app version before applying newer features. Numerical requirements below retain their original scope.
The official RAM tiers are workload-scoped: the 4 GB tier assumes a basic deployment with accelerator-backed detection. An 8 GB Zima host also runs the OS and other containers. Shared-memory allocations and detection benchmark results are not whole-server camera-capacity guarantees.
| Requirement | Official minimum | What this supports |
|---|---|---|
| Basic RAM baseline | 4 GB | Official planning scope: a few cameras, a dedicated object-detection accelerator and no enrichments. |
| RAM with enrichments | 8 GB minimum; 16 GB recommended for broader workloads | Do not label the 16 GB recommendation as a universal minimum. |
| CPU instruction set | AVX and AVX2 required | Instruction support differs from numerical CPU-core count. |
| CPU core count | No numerical official minimum published. | Camera activity, codec/decoding and detector configuration drive sizing. |
| Storage capacity | No numerical official minimum published. | Bitrate, recording mode and retention determine capacity; keep config/database and video storage separate. |
| Container / runtime | Official ghcr.io/blakeblackshear/frigate container | Docker Compose is recommended; choose release/architecture/accelerator variant and pass required devices. |
| MQTT / integration | Broker optional for Frigate; required for Home Assistant integration | Connect Frigate and Home Assistant to the same broker when using that integration. |
When to upgrade your hardware
Use observed Frigate workload pressure to decide when an upgrade is warranted.
Detection falls behind when several cameras see motion
Decode processes saturate CPU
Retention cannot fit available recording storage
Confirm that hardware decoding is actually active, the GPU device is accessible and stream presets match the codec. Software fallback can dominate CPU.
High-resolution streams or unsupported codec combinations.Use observed bitrates and measured retained footage; add capacity or adjust recording policy while retaining space for normal operation.
Continuous recording and longer retention.Plan hardware growth with confidence
Address storage, memory, compute and deployment limits separately.
Separate active data from recordings
Keep config/database on durable low-latency storage and put recordings on a drive sized for the measured write workload.
ZimaBoard 2 with a SATA SSD/HDD suited to retention.Add RAM for enrichments and shared services
Choose 16 GB when enrichment models and other containers pressure an 8 GB host; the N150 CPU remains unchanged.
ZimaBoard 2 1664.Expand video retention across more drives
Choose storage topology for sustained writes and retention; protect critical exports independently.
ZimaCube 2 Standard.Scale processing after validating acceleration
Use stronger CPU/iGPU resources for measured workload pressure. Add a discrete GPU only for a verified backend/model requirement.
ZimaCube 2 Pro; separately validate any GPU expansion.Can it run on ZimaOS?
A specific public Frigate page is confirmed in the official ZimaOS App Store. The upstream project prefers low-overhead hardware access; validate the ZimaOS kernel/driver, container permissions and storage configuration rather than treating one-click availability as a throughput guarantee.
Install Frigate from the ZimaOS App Store
Open the Frigate listing, install the app and verify persistent config/recording paths, detector device access, shared memory and available network ports. Match settings to the chosen release.
Open Frigate in the ZimaOS App Store ↗Use the official Frigate deployment instructions
Keep the selected stable release, persistent paths and companion services aligned with upstream documentation.
Review Frigate official installation ↗Review official Frigate deployment details
Keep Docker image selection, accelerator pass-through, shared memory, authentication and storage aligned with the upstream installation guide.
Review Frigate deployment details ↗Which Zima hardware fits Frigate?
Start with the lowest reasonable host for the actual workload. Product specifications were checked against the current product pages.
Which workload best matches your Frigate deployment?
Small camera setup with controlled detection
Use Intel acceleration, conservative detection FPS and separate recording storage.
- Workload optionZimaBoard 2 832
- Workload optionZimaBoard 2 1664
Longer retention or heavier mixed processing
Choose multi-drive capacity first; select Pro when measured compute load also warrants it.
- Workload optionZimaCube 2 Standard
- Workload optionZimaCube 2 Pro
These are practical workload recommendations, not official app requirements, compatibility certification, measured capacity limits or performance guarantees. Include all co-hosted services and independent backups.
| Zima hardware | Best for | Example workload | Core configuration | Recommended boundary | Next step |
|---|---|---|---|---|---|
| ZimaBoard 2 832 | Small, tuned NVR workload | Basic Frigate, Intel acceleration and separately provisioned recording storage. |
|
8 GB does not guarantee camera count or leave enough room for every enrichment; validate acceleration and peak memory. | Get Now |
| ZimaBoard 2 1664 | More memory headroom | Frigate enrichments or a modest shared smart-home stack. |
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16 GB matches the RAM recommendation, but CPU and detector throughput remain workload-dependent. | Get Now |
| ZimaCube 2 Standard | Storage-focused recording retention | Multi-drive recordings with SSD-backed application data. |
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Its 8 GB base memory is lower than the Board 1664; storage expansion does not solve every processing limit. | Get Now |
| ZimaCube 2 Pro | Heavier consolidated surveillance | More CPU headroom with a larger recording topology. |
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No fixed camera count is promised; validate codecs, detection models and shared acceleration use. | Get Now |
What the Press Says
Highlights from trusted reviewers worldwide.
“ZimaCube 2: Not just another NAS, tested with 25TB storage, local AI agents, 4K transcoding, and real homelab workflows.”Read full review
“The ZimaBoard 2 is a compact x86 server board that can be turned into a mini NAS, home server, media box, or self-hosting hub.”Read full review
“ZimaCube 2: A modern, high-performance NAS with plenty of room to grow—built for users who want more than basic storage.”Read full review
“Coverage focused on ZimaCube 2's open hardware foundation, no monthly fee, and self-hosting flexibility.”Read full review
Loved by the Community
Stories and reviews from people who build with Zima every day.
★★★★★
Zima Blade Little yet Powerful
Maybe I am not digital natives but I live with PCs since 12 years old in 1984 when IBM PC clone come to my home. Many years have passed and many operating system I've tried. For me Zima blade and CasaOS was a quantum leap for home PC enthusiast and server lab machine to make me stay curious and relevant for this era.
★★★★★
Very good!!
I use ZimaCube Pro as 5th Proxmox cluster node. It runs several VMs and containers, including a VM with GPU passthrough to run a self-hosted LLM. A specific LXC container runs a Samba server for NAS capabilities using four of six RAID 6 SATA HDDs with ZFS.
★★★★★
Great innovation for mini server!
It is very useful and makes a powerful mini server for many purposes, including university and college students in engineering and electronics. Thank you so much for making this server.
★★★★★
Avaliação ZimaBoard 2
Construí um servidor de uso pessoal. O desempenho está muito bom e funciona perfeitamente onde quer que eu esteja. A surpresa é não dependermos de grandes estruturas para termos nosso próprio servidor de dados. Como iniciante, estou gostando bastante do ZimaOS, pois ele é simples e eficiente.
Frequently asked questions
Answers to Frigate RAM, CPU, storage, Docker, database and ZimaOS sizing questions.
What is the official Frigate RAM minimum?
The planning guide gives 4 GB for a basic setup with a few cameras, dedicated detection acceleration and no enrichments. It gives an 8 GB minimum for enrichments and recommends 16 GB for broader workloads. These scopes should not be collapsed into one universal figure.
Does Frigate require AVX2?
Yes. Current official planning documentation requires AVX and AVX2. Check the actual CPU instruction set; an older low-power x86 chip is not necessarily compatible just because Docker starts.
Are decoding and object detection the same GPU task?
No. FFmpeg decoding handles the camera video pipeline, while the detector performs model inference on selected regions. Configure and validate each backend independently.
How much recording storage does Frigate need?
For continuous recording, a measured 1 Mb/s stream uses approximately 10.8 decimal GB per day. Multiply aggregate bitrate by retention, then add overhead, clips, database/model storage and working headroom. Event-only retention depends on observed activity.
Do I need a Coral or NVIDIA GPU?
Neither is a universal requirement. Choose a supported detector such as Intel OpenVINO when suitable. Current hardware guidance no longer treats Coral as the default choice for most new installations; model and backend compatibility matter.
Can ZimaBoard 2 run Frigate?
It is a practical candidate for a small tuned setup with Intel acceleration, appropriate device access and a recording drive. Measure peak motion, inference and memory before expanding cameras or enrichments.
Why is a camera-count estimate insufficient?
Two installations with the same camera count can have different resolution, FPS, codecs, motion and simultaneous detections. Retention also changes disk requirements independently of compute.
When should I choose ZimaCube 2?
Choose Standard for multi-drive recording capacity. Choose Pro when real processing pressure and service consolidation warrant stronger CPU resources, while validating detector and decoding support.
What sources informed this Frigate hardware guide?
Official project requirements, installation/configuration documentation, repository/release information and the current Zima product pages were checked on October 23, 2026. Practical hardware recommendations are editorial sizing guidance rather than upstream minimums.
