Bazarr's performance guide says synchronization may extract audio and cause massive CPU/network usage, while inspecting embedded subtitles can be resource-intensive on low-powered devices. If these jobs are routine and visibly delay the rest of the server, additional CPU headroom is justified.
For large libraries, frequent subtitle alignment or users who keep embedded-subtitle inspection enabled.Bazarrのハードウェア要件：CPU、RAM、ストレージ、字幕同期
字幕検索、同期、埋め込み字幕のスキャン、Sonarr／Radarrとの連携、およびZimaOSサーバーの選択に必要なBazarrのハードウェア要件を確認しましょう。
Bazarr hardware requirements at a glance
Bazarr does not publish a numeric minimum CPU or RAM specification. The project supports Linux, Windows, macOS and Raspberry Pi-class systems, and its own performance guide discusses tuning for low-powered devices. On ZimaOS, hardware demand is usually modest until large libraries, frequent missing-subtitle searches, embedded-subtitle scans, subtitle synchronization or a larger Sonarr/Radarr media stack increase CPU, storage I/O and network activity.
- CPU
- No official numeric CPU minimum is published. Bazarr can run on low-powered hardware, but its official performance guide warns that automatic subtitle synchronization may extract audio and create heavy CPU and network use. Embedded-subtitle scanning can also be resource-intensive on low-powered devices.
- RAM
- No official numeric RAM minimum is published. For ZimaOS, choose memory for the complete media-automation stack rather than Bazarr alone: Bazarr normally runs beside Sonarr and/or Radarr and may share the server with downloaders, Plex, Jellyfin, Emby or other containers.
- Storage
- Bazarr stores persistent configuration and its database under the application config path while reading the media paths managed by Sonarr and Radarr. It does not require a second copy of the media library. Keep Bazarr config persistent and map the same movie/TV paths consistently across the containers.
- Network
- Bazarr publishes no fixed Mbps requirement. It needs reliable access to Sonarr/Radarr, subtitle providers and the media files it analyzes. Remote or cloud-hosted media can make scanning and subtitle synchronization more network-intensive than the Bazarr web interface itself.
- GPU
- Bazarr itself does not require a dedicated GPU for ordinary subtitle management. An optional Whisper/ASR workflow can use a separate CPU or NVIDIA-GPU transcription service; that is an additional service and should not be presented as a baseline Bazarr requirement.
- Best Zima starting point
- ZimaBoard 2 832 is already a strong starting point for Bazarr with Sonarr/Radarr and a normal home media library. Move to 1664 for more co-hosted containers and memory headroom; choose ZimaCube 2 primarily when the media library, drive count or broader media-server workload needs an integrated multi-drive NAS.
From official requirements to the right setup
Bazarr sizing starts with the media-management workflow, not with playback resolution. The important questions are how large the Sonarr/Radarr library is, how often Bazarr searches and scans, whether subtitle synchronization is enabled and where the media and Bazarr database live.
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Official requirements
Confirm the deployment first. Bazarr is a companion to Sonarr and Radarr and does not independently discover movies and series from raw folders. Make sure the ZimaOS Bazarr container can reach the Sonarr/Radarr APIs and that the media path mappings refer to the same files those applications manage.
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Confirm your needs
Start with normal subtitle searching and library updates, then observe the scheduled workload. The official Bazarr performance guide recommends reducing search frequency or enabling Adaptive Searching when many subtitles are missing because repeated scheduled work can become unnecessary load on low-powered devices.
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Leave room to grow
Treat embedded-subtitle scans and automatic subtitle synchronization as the main compute triggers. Bazarr states that embedded subtitle detection can be resource-intensive, while synchronization may extract audio to align speech fragments and can produce substantial CPU and network usage.
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Run it on ZimaOS
Install Bazarr from the ZimaOS App Store, keep its /config data persistent, map movie and TV storage consistently with Sonarr/Radarr, then test a representative library scan, missing-subtitle search and synchronization job. Upgrade only if those measured jobs or the rest of the media stack create a repeatable bottleneck.
Check every playback client
- Sonarr, Radarr or both and whether they run on the same ZimaOS host
- Number of indexed movies, series and episodes
- Number of missing or wanted subtitles
- Subtitle search and upgrade schedule frequency
- Whether embedded-subtitle scanning is enabled
- Whether automatic subtitle synchronization is enabled
- Media location: local HDD/SSD, NAS share or cloud-mounted storage
- Other concurrent apps such as downloaders, Plex, Jellyfin or Emby
Official minimum requirements
Bazarr's current official website, project repository, installation wiki and Docker documentation do not publish a numeric minimum CPU, RAM or network specification. Official guidance instead documents supported platforms, container architectures, dependencies, path mapping and performance-tuning options for low-powered systems. Fixed CPU or RAM numbers from third-party pages should not be labeled as Bazarr's official requirements.
Use the official documentation as the software and workflow baseline, then size ZimaOS from library scale and enabled features. Bazarr's own performance guide confirms that low-powered devices such as Raspberry Pi are viable, while audio extraction for subtitle synchronization and embedded-subtitle scanning are the workloads most likely to increase CPU, storage and network demand. The SystemRequirementsLab page for 'The Bazaar' is an unrelated PC game and must not be used as a Bazarr source.
| Requirement | Official minimum | What this supports |
|---|---|---|
| CPU | No numeric minimum published | Bazarr's official performance guide explicitly discusses users running on low-powered devices such as Raspberry Pi. CPU demand rises with subtitle synchronization, audio extraction, embedded-subtitle inspection and large scheduled workloads. |
| RAM | No numeric minimum published | Current official Bazarr installation and Docker material does not specify a fixed RAM floor. Practical memory should include Sonarr/Radarr and the other containers that normally share the same server. |
| Storage / database | Persistent /config plus access to Sonarr/Radarr media paths | LinuxServer's Bazarr image stores configuration under /config. Bazarr reads the movies and series managed by Sonarr/Radarr rather than maintaining a separate media copy. Keep path mappings consistent and the application database on reliable persistent storage. |
| Network | No universal Mbps minimum published | Bazarr needs network access to Sonarr/Radarr and subtitle providers. Cloud or remote media can make scans and synchronization network-heavy because Bazarr may inspect media or extract audio during subtitle-processing tasks. |
| Container architecture | x86-64 and arm64 supported by the LinuxServer image | LinuxServer's current Bazarr image publishes both amd64 and arm64 variants, so a dedicated x86 desktop-class CPU is not required simply to run the application. |
| GPU | Not required for core Bazarr; optional for external Whisper/ASR | Bazarr's Whisper provider documentation connects to a separate ASR service that can run on CPU or reserve an NVIDIA GPU. That optional transcription workload should be sized separately from ordinary subtitle search and management. |
When to upgrade your hardware
Upgrade Bazarr hardware for a measured media-automation bottleneck, not because subtitle files themselves are large. The strongest triggers are expensive subtitle-processing jobs, a larger shared media stack and storage/network latency during scans.
Subtitle synchronization or embedded scans repeatedly saturate the CPU
Bazarr is only one part of a much larger media stack
Large or remote libraries make scanning and file access slow
Sonarr, Radarr, a downloader, media server, indexers and other containers all share CPU and memory. Bazarr itself can be lightweight, but the aggregate workload can justify more RAM and CPU even when Bazarr alone would not.
For always-on ZimaOS hosts running a complete automated media stack.Frequent disk indexing, cloud-mounted media or remote NAS paths can make subtitle detection and synchronization I/O- or network-bound. Upgrade storage layout or networking when measurements show file access, not CPU, is the constraint.
For multi-drive libraries, remote shares and cloud-mounted media collections.Plan hardware growth with confidence
Bazarr scales best when its configuration/database, media paths, scheduled jobs and optional transcription services are treated as separate resources. This keeps a larger library from forcing an unnecessary full-server upgrade.
Keep Bazarr config and database on reliable persistent storage
The Docker image keeps application state under /config. Bazarr's current Synology guidance also documents SQLite locking problems when cloud backup software accesses bazarr.db, which is a reminder that database placement and file-lock behavior matter more than raw capacity.
Use persistent local SSD/eMMC/NVMe or another reliable local filesystem for application state; back it up in a way that does not interfere with a live SQLite database.Tune search schedules before buying a faster CPU
Bazarr recommends reducing missing-subtitle search frequency and enabling Adaptive Searching when many subtitles are wanted. This can remove unnecessary periodic work without changing hardware.
Measure scheduler load first. A low-power server may remain sufficient after search and scan intervals are tuned to the real library.Keep media path mappings consistent across containers
Bazarr depends on Sonarr/Radarr's indexed media and must be able to reach the same files through correct Docker path mappings. ASUSTOR's current Bazarr package similarly maps Bazarr /tv and /movies to Sonarr/Radarr media locations.
Prefer clear local or NAS paths and consistent mount points. Path mapping errors are configuration failures, not reasons to buy more CPU or RAM.Separate optional Whisper transcription from normal Bazarr sizing
Bazarr can use an external Whisper/ASR endpoint for subtitle generation. The official provider guide shows separate CPU and NVIDIA-GPU service examples, so transcription compute can be scaled independently of the Bazarr container.
Only add dedicated GPU or major CPU capacity when local ASR is a real requirement. Ordinary provider-based subtitle search does not need that hardware.Can it run on ZimaOS?
Bazarr is available in the ZimaOS App Store. A correct ZimaOS deployment depends more on container networking and path mappings than on unusual hardware requirements.
Install Bazarr from the ZimaOS App Store
Use the ZimaOS Bazarr app as the application layer, then complete the Bazarr WebUI setup and connect Sonarr, Radarr or both.
Open Bazarr in the ZimaOS App StoreConnect Sonarr and Radarr through reachable container addresses
Bazarr's official setup guide warns that Docker containers cannot use 127.0.0.1 or localhost to reach a different container on the same host. Use the correct container hostname, bridge-network address or host address and the Sonarr/Radarr API ports.
Read Bazarr's official setup guideMap movies and TV folders consistently
Bazarr manages media already indexed by Sonarr and Radarr, so it needs access to matching movie and TV paths. Keep /config persistent and verify that Bazarr can read and write subtitle files beside the media where required.
Read the Bazarr Docker installation guideChoose Zima hardware for your Bazarr workload
Choose hardware from the complete media-automation stack. Bazarr itself can run on low-powered systems, so additional CPU, RAM, drive bays or 10GbE should correspond to a larger library, expensive synchronization/scanning work or other applications running on the same ZimaOS host.
Is Bazarr mainly running with Sonarr/Radarr on a normal home media library, without heavy subtitle synchronization or a large multi-service workload?
Yes — ordinary subtitle automation is the main job
Bazarr's core workload is light enough that an efficient ZimaBoard 2 is normally the appropriate class of hardware. Choose between 8 GB and 16 GB primarily for the other containers sharing ZimaOS.
- Bazarr + Sonarr/Radarr + a few light servicesZimaBoard 2 832
- Larger media-automation stack or more memory headroomZimaBoard 2 1664
No — the server also needs a large multi-drive media library or substantially heavier concurrent services
Move to ZimaCube 2 for integrated storage growth and broader server headroom. Choose Pro only when the complete workload demonstrates a need for more CPU, RAM, SSD expansion or 10GbE; Bazarr alone does not justify it.
- Large local media library with integrated multi-drive storageZimaCube 2 Standard
- Heavy multi-service media server, faster storage workflows or 10GbE needZimaCube 2 Pro
These are workload profiles, not Bazarr-certified minimums or guaranteed library-size limits. Bazarr publishes no fixed CPU/RAM floor. Real resource use depends on library size, missing-subtitle count, scan schedules, synchronization, provider behavior, media path latency and the other containers sharing the server.
| Zima hardware | Best for | Example workload | Core configuration | Recommended boundary | Next step |
|---|---|---|---|---|---|
| ZimaBoard 2 832 | A compact Bazarr, Sonarr and Radarr host for a normal home media library with a few additional lightweight ZimaOS services. | Automatic subtitle search, normal scheduled scans, light synchronization and local/NAS media paths without a large number of heavy concurrent containers. |
|
Choose additional hardware for Sonarr/Radarr, downloaders, media servers or frequent subtitle-processing jobs, not because Bazarr has an 8 GB requirement; it does not publish one. | Get Now |
| ZimaBoard 2 1664 | Bazarr inside a broader always-on media-automation stack that benefits from more container memory headroom. | Bazarr, Sonarr, Radarr, downloaders, indexers and several other services running together, with larger libraries or more background jobs. |
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Do not treat 16 GB as a Bazarr requirement. Choose this model when the complete ZimaOS stack needs the RAM headroom. | Get Now |
| ZimaCube 2 Standard | A larger Bazarr/Sonarr/Radarr media system where integrated multi-drive storage is more important than extra Bazarr compute. | Large movie and TV libraries, several media-automation services, local bulk storage and routine subtitle scanning on a single NAS host. |
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Choose Standard because the media library and broader NAS workflow need the drive bays and server headroom, not because Bazarr itself requires a Core i3 or six-bay NAS. | Get Now |
| ZimaCube 2 Pro | A heavy multi-service media NAS where Bazarr shares the host with demanding media, indexing, VM or storage workloads and 10GbE is independently useful. | Large multi-drive media library, frequent background automation, media server workloads, faster SSD workflows and many concurrent ZimaOS services. |
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Usually excessive for Bazarr alone. Choose Pro for the combined media-server, storage or networking workload rather than expecting subtitle files to benefit from 10GbE. | 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
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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.
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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.
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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
These answers separate Bazarr's documented behavior from third-party hardware claims and explain when ZimaOS hardware actually needs to scale.
How much RAM does Bazarr need?
Bazarr does not publish a numeric RAM minimum in its current official installation or Docker documentation. It is known to run on low-powered systems, but a ZimaOS host normally also runs Sonarr, Radarr and other media services. Treat 8 GB on ZimaBoard 2 as a practical platform configuration, not a Bazarr minimum; choose more memory for the complete container stack.
What CPU does Bazarr require?
There is no official CPU model, core count or clock-speed minimum. Bazarr's own performance guide discusses Raspberry Pi and other low-powered devices, which shows that ordinary subtitle management can be lightweight. CPU becomes more important when automatic synchronization extracts audio, embedded subtitles are scanned across a large library or many other applications are active at the same time.
Does Bazarr need a GPU?
No for normal subtitle searching, downloading, naming and library management. Bazarr's optional Whisper provider connects to a separate ASR service that can run on CPU or use an NVIDIA GPU. A dedicated GPU should therefore be sized for local transcription or other server workloads, not for core Bazarr.
Can ZimaBoard 2 run Bazarr?
Yes. Bazarr officially supports low-powered platforms and LinuxServer publishes an amd64 Docker image, while ZimaBoard 2 provides an Intel N150, 8 GB or 16 GB RAM and dual 2.5GbE. For most users the main concern is configuring Sonarr/Radarr connectivity and media path mappings correctly rather than raw hardware capability.
Why can Bazarr use high CPU during subtitle synchronization?
Bazarr's official performance guide says automatic subtitle synchronization may need to extract an audio track to detect speech fragments and align subtitles, which can create heavy CPU and network use. This is a workload spike, not evidence that Bazarr always needs a powerful CPU.
Why can embedded-subtitle scanning be slow on a NAS?
Bazarr needs to inspect video containers such as MKV or MP4 to identify embedded subtitles. Its performance guide states that this can be resource-intensive on low-powered devices and can also be problematic with cloud-hosted media. Disable or reduce this work if embedded subtitle detection is not important to the workflow.
Does Bazarr need Sonarr and Radarr?
Bazarr is designed as a companion to Sonarr and Radarr. Its project documentation says it does not scan the disk to discover series and movies independently; it manages titles indexed in Sonarr and Radarr. Current Plex and Jellyfin integrations also still require the Sonarr/Radarr workflow.
When should I choose ZimaCube 2 instead of ZimaBoard 2 for Bazarr?
Choose ZimaCube 2 when the broader media system needs integrated multi-drive storage, a much larger local library or more concurrent services. Bazarr alone is not a reason to buy a six-bay NAS. Standard is the practical storage-growth step; Pro should be reserved for a demonstrated need for more CPU, RAM, SSD expansion or 10GbE in the complete server workload.
What sources and further reading informed this Bazarr hardware guide?
Bazarr's official website, repository, installation wiki and Performance Tuning guide are the primary sources. LinuxServer's current Bazarr image documents the supported amd64/arm64 container architectures and /config behavior. The ZimaOS App Store confirms a Bazarr app is available. The ASUSTOR page is useful as another current NAS/Docker deployment example but does not define Bazarr CPU or RAM minimums. The 2022 DietPi thread is retained only as historical Raspberry Pi installation context. The supplied SystemRequirementsLab URL is deliberately excluded from hardware evidence because it refers to the unrelated PC game The Bazaar, not the Bazarr subtitle manager. Current Zima product pages are the source of ZimaBoard 2 and ZimaCube 2 specifications.
