toolchest_

Measured on a real homelab

Jellyfin RAM & CPU requirements (measured)

On our homelab it uses about 85 MB of RAM on a normal hour, 143 MB in busy hours, and peaked at 468 MB over the last 30 days (small library: 9 video files (94 GB)).

What it really uses (process memory)

Typical (median)
85 MB
Average
87 MB
Busy hours (95th percentile)
143 MB
Highest recorded
468 MB
As docker stats shows it (with disk cache)
median 168 MB · peak 664 MB
Window
720 hours measured, up to Sep 26, 2026
Version
12.1.0
Stack (all summed)
jellyfin
Workload
small library: 9 video files (94 GB)
Hardware
Intel i5-10600K · 23 GB RAM · Docker (Coolify)

Caveat (Oct 2, 2026): these figures count process memory held in RAM. When the server is under memory pressure, idle apps get part of their memory swapped out and it was not being counted, so the "typical" figure may be too low; the peak is reliable. We now measure RAM plus swap and will update these numbers.

What makes it grow

Each additional concurrent transcoding stream significantly increases CPU/GPU and RAM usage; 4K streams and subtitle burning are especially demanding.

Sizing it

Our rule of thumb: plan for the highest process memory recorded plus 25% headroom: 640 MB. Our workload is small — scale it with the factors above before buying hardware.

Combine it with other apps in the resource calculator →

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How we measure

Memory per container from Netdata on the same server, summed across the whole stack (app, database and cache) hour by hour. The main figures are the processes' own memory (anonymous memory: heap, stacks). The docker stats figure is higher because it also counts active disk cache — which Linux gives back when it needs it — and shared memory such as PostgreSQL's shared buffers. Hours where the main container had no data are left out, not counted as zero. Re-measured with a script, not by hand.

Other measured apps