PyLoad Hardware Requirements: RAM, CPU, Storage & Download Throughput
Plan PyLoad hardware for RAM, CPU, downloads, extraction, plugin workloads, storage, and practical ZimaOS deployment recommendations.
PyLoad hardware requirements at a glance
Size PyLoad from verified upstream requirements first, then add headroom for the workload and persistent data.
- RAM
- No numerical official minimum published
- CPU
- No numerical official minimum published
- Storage
- Size /downloads plus /config and temporary/extracted files
- Runtime
- Python 3.9+
- Ports
- 8000 web UI; 9666 Click'N'Load
- Best Zima starting point
- ZimaBoard 2 832
From official requirements to the right setup
Start with verified upstream facts for PyLoad, then size the workload rather than copying a container or app-store resource label.
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Official requirements
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Confirm your needs
-
Leave room to grow
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Run it on ZimaOS
Check every playback client
- Simultaneous downloads
- Download bandwidth
- Archive extraction
- Plugin set
- Premium hoster usage
- Download retention
- Temporary/extract space
- Backup strategy
Official minimum requirements
The current pyLoad project publishes runtime and deployment requirements but no numerical whole-host CPU, RAM, or disk minimum.
The 256 MB value on the ZimaOS App Store listing is store metadata, not a pyLoad upstream official minimum.
| Requirement | Official minimum | What this supports |
|---|---|---|
| No numerical official minimum published | Download management is light; extraction/plugins add bursts. | |
| No numerical official minimum published | Upstream calls pyLoad lightweight but does not define a host floor. | |
| Python 3.9 or newer | Python below 3.9 is unsupported by current pyLoad-ng. | |
| linuxserver/pyload-ng | Listed by upstream under Docker Images. | |
| 8000 | Web interface. | |
| 9666 | Click'N'Load integration. | |
| Not required | No GPU workload documented. |
When to upgrade your hardware
Extraction CPU pressure
Storage growth
Multi-app contention
Plan hardware growth with confidence
Fast active-download disk
Place active downloads/extraction on SSD rather than eMMC.
SATA SSD or NVMeMore RAM for shared hosts
Useful with many plugins and containers.
ZimaBoard 2 1664Large download retention
Use multi-bay storage for long-term files.
ZimaCube 2 StandardMore CPU for extraction
Useful for repeated archive extraction/checksum work.
ZimaCube 2 ProCan it run on ZimaOS?
Install PyLoad from the ZimaOS App Store
A specific public PyLoad App Store page is verified.
Open PyLoad in the ZimaOS App Store โFollow current pyLoad-ng runtime
Current upstream requires Python 3.9+ and documents Docker/Compose.
Open PyLoad source โKeep downloads persistent
Map configuration and download directories to durable host storage.
Review PyLoad Docker guidance โZima hardware for PyLoad
PyLoad itself is light; choose hardware mainly for bandwidth, extraction, retained files, and the rest of the automation stack.
Choose by workload
ZimaBoard is sufficient with attached SATA storage.
Storage topology and CPU throughput become more important.
The ZimaOS store 256 MB label is not treated as an upstream official minimum.
| Zima hardware | Best for | Example workload | Core configuration | Recommended boundary | Next step |
|---|---|---|---|---|---|
| ZimaBoard 2 832 | Light self-hosted services and small download/transfer workloads | One light app or a small home-server stack |
|
8 GB RAM and a 4-core N150 can limit CPU-heavy extraction, AI, and large multi-service stacks | Get Now |
| ZimaBoard 2 1664 | Memory-heavier download automation and multi-container workloads | Apps benefiting from 16 GB RAM without needing a much faster CPU |
|
CPU throughput is unchanged from the 832 model | Get Now |
| ZimaCube 2 Standard | Storage-heavy downloads and media libraries | Large persistent data sets where drive bays matter most |
|
8 GB RAM can be less suitable than ZimaBoard 2 1664 for memory-heavy services | Get Now |
| ZimaCube 2 Pro | CPU-heavier extraction and higher-concurrency workloads | Stronger CPU plus expanded storage and networking |
|
16 GB RAM can still constrain large local AI workloads | Get Now |
What the Press Says
Highlights from trusted reviewers worldwide.
โZimaCube 2: Not just another NAS, tested with 25TB storage, local AI agents, 4K transcoding, and real homelab workflows.โRead full review
โThe ZimaBoard 2 is a compact x86 server board that can be turned into a mini NAS, home server, media box, or self-hosting hub.โRead full review
โZimaCube 2: A modern, high-performance NAS with plenty of room to growโbuilt for users who want more than basic storage.โRead full review
โCoverage focused on ZimaCube 2's open hardware foundation, no monthly fee, and self-hosting flexibility.โRead 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.
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.
Avaliaรงรฃo ZimaBoard 2
Construรญ um servidor de uso pessoal. O desempenho estรก muito bom e funciona perfeitamente onde quer que eu esteja. A surpresa รฉ nรฃo dependermos de grandes estruturas para termos nosso prรณprio servidor de dados. Como iniciante, estou gostando bastante do ZimaOS, pois ele รฉ simples e eficiente.
Frequently asked questions
How much RAM does PyLoad need?
No numerical whole-host RAM minimum is published upstream.
How many CPU cores does PyLoad need?
No numerical official CPU minimum is published.
Which Python version does current PyLoad require?
Python 3.9 or newer.
Which Docker image does the project list?
linuxserver/pyload-ng.
Which ports are used?
8000 for web UI and 9666 for Click'N'Load in the upstream Compose example.
Can ZimaBoard 2 832 run PyLoad?
Yes for normal downloader workloads with downloads on attached storage.
Does PyLoad need a GPU?
No.
When should I choose ZimaCube 2?
When retained files or extraction/storage throughput become the bottleneck.
