Tag: Jellyfin

Jellyfin is the open-source media server Chikewa tests for home movie and TV libraries. Guides cover the Docker Compose setup, hardware transcoding and real resource usage.

  • Jellyfin vs Plex: Which One Fits Your Home Server?

    Jellyfin vs Plex: Which One Fits Your Home Server?

    The honest question is not “which is better” — it is “which fits how I watch and what I am willing to pay.” Jellyfin and Plex do almost the same job (turn a folder of media into a streamable library), but they make very different bets on price, on who controls the transcoding, and on how much you are expected to trust the vendor. This is a straight comparison across the things that actually matter, without a crown, so you can pick the one that fits your household.

    Beginner · 7 min · Media Server

    Price: the clearest difference

    Jellyfin is free, open source, and free forever. There is no premium tier, no monthly fee, and no feature held back behind a paywall. Everything in the server is available to everyone.

    Plex has a free tier, but the features people actually want — transcoding on the server, direct play to certain clients, and direct streaming to some devices — live behind Plex Pass, a paid subscription. If you run Plex the way most people want to, you are paying a recurring fee. For a home server you own, that is the single biggest practical difference, and for a lot of people it is the deciding one.

    Transcoding: who does the work

    This is the technical heart of the difference. Both apps can direct-play (send the file as-is, cheap on the CPU) and transcode (re-encode for a device that cannot play the source, expensive on the CPU).

    Jellyfin lets you use your own hardware encoder — Intel Quick Sync, NVIDIA, AMD — for the transcoding, and it is free to do so. The ceiling on how many 4K streams you can transcode at once is set by your hardware, and you can measure it. On a modest 4-core Intel box with a basic iGPU we measured three concurrent 4K-to-1080p transcodes holding real time before it started to slip — that is the number a dedicated 4K transcoding test on the same box confirms.

    Plex bundles a licensed encoder and handles the hardware acceleration for you, which is convenient — but the advanced transcoding and hardware-accelerated paths are part of the paid tier. The trade-off is that Plex’s client experience is generally smoother and more polished, at the cost of the subscription.

    Clients and ease of use

    Plex wins on the out-of-the-box experience. Its apps are polished, the setup wizard is friendly, and the metadata, artwork and matching are excellent with almost no configuration. If you want the least-friction path from “folder of movies” to “it just works on every screen,” Plex is the smoother ride.

    Jellyfin’s clients are good but a notch behind in polish. The browser player works everywhere, the mobile apps are solid, and most major smart TVs either have a native app or can run it in the browser. If you are willing to spend an evening configuring it, you get the full feature set for free. The setup is well documented in the Jellyfin Docker guide.

    Where each one fits

    If you…Reach forWhy
    Do not want to pay a subscription and you are comfortable configuringJellyfinFull features, free, and you control the hardware transcoding
    Want the smoothest setup and you do not mind a subscriptionPlexPolished clients, great metadata, minimal fiddling
    Have a capable iGPU or GPU and want to transcode 4KJellyfinFree hardware transcoding, and you can measure your ceiling
    Mostly watch on a smart TV and want it to just workEitherBoth work; Plex is slightly smoother, Jellyfin is free
    Want everything to stay on your own hardware, no vendor cloudJellyfinNo account, no service dependency, open source

    The privacy and control angle

    Both run the media server on your own machine, so your files stay with you in both cases. The difference is in the control plane. Jellyfin has no account and no vendor service in the path of your data — the server is yours entirely. Plex ties the premium experience to a Plex account and, for remote access, routes through its infrastructure. If “no third party touches this” is a hard requirement for you, that is a point for Jellyfin, independent of price.

    Bottom line

    Neither is wrong. Jellyfin is the choice when you want full features, free, on your own terms, and you are happy to spend a little time on setup — it is the natural fit for a home-server person who is already running Docker and does not mind configuring. Plex is the choice when you want the most polished, lowest-friction experience and are comfortable paying a subscription for it. For the Chikewa audience — people who run their own boxes and like to understand what they are running — Jellyfin is usually the better match, and the hardware is where the real capability lives, not the app.

  • Access Jellyfin from Outside Your Home Network

    Access Jellyfin from Outside Your Home Network

    A Jellyfin server that only works on your home network is half the job. The real point is watching from the phone on the train, from the laptop at a friend’s place, or from the TV when you are travelling. Getting there without turning your house into an open target comes down to choosing one of three access paths — and for most people the right answer is the one that opens no ports at all. This article walks through the three, with the real trade-offs, and tells you which one fits your setup.

    Intermediate · 8 min · Networking

    The three ways to reach it from outside

    There are really only three approaches, and they differ in one fundamental way: who connects to whom.

    • Port forwarding (the old way). You open a port on your router so the internet can find your server. It works, but it exposes a port to the whole world, which is why it needs a reverse proxy, HTTPS, and careful firewall rules to be safe.
    • A private mesh (Tailscale). Your phone and your server both join a private encrypted network. They talk to each other directly, and nothing is exposed to the public internet. This is the path most home-server setups should use.
    • A tunnel (Cloudflare Tunnel). Your server initiates an outbound connection to Cloudflare’s edge, and your browser reaches the server through that. Like the mesh, it needs no open inbound ports, but it routes traffic through Cloudflare rather than a direct peer-to-peer link.

    The mesh and the tunnel both avoid open inbound ports, which is the single most important safety property. Port forwarding is the one you reach for only when you have a specific reason to, such as needing a plain domain with a normal client that cannot install the mesh app.

    For a home server the Tailscale approach is the best fit, because it is the safest with the least moving parts. Install the agent on the server, install the app on your phone and laptop, sign in with the same account, and the devices see each other on a private network with their own addresses. You then point your Jellyfin client at the server’s private address and you are streaming, with every byte encrypted and with nothing on your router opened to the outside.

    Two things make this the default recommendation. First, it is outbound-only: your server initiates the connection, so there is no inbound port to secure. Second, it is private by construction — the traffic never transits a third-party network, it goes directly between your own devices (with an encrypted relay used only when two devices cannot reach each other directly). If you want a working, tested setup for this, the Tailscale in Docker guide has the exact compose file and the one step that trips people up (approving the login in the console).

    The honest trade-off: every device you want to stream from needs the Tailscale app. That is not a problem for a household of phones and laptops, but a smart TV that cannot install the app is out — for that you pair the mesh with one of the other methods, or you accept that the TV only works at home.

    The alternative that needs no app on the client: Cloudflare Tunnel

    When you need to reach the server from a device that cannot run the mesh app — a browser on a work computer, some TVs, a tablet without the app — a tunnel is the better fit. Your server keeps an outbound connection to Cloudflare, and you reach Jellyfin through a real domain over HTTPS. There is no open inbound port, the certificate is handled for you, and any device with a browser can connect.

    The trade-offs are that the traffic transits Cloudflare’s edge (fine for most, but it is a third party in the path), and you need a domain pointed at Cloudflare. If that fits your setup, the Cloudflare Tunnel in Docker guide walks through the tunnel and the compose wiring. It pairs naturally with a reverse proxy so the same domain also fronts your other services — see the Caddy reverse proxy guide for that layer.

    Port forwarding, and when you actually need it

    Port forwarding is still valid in a narrow set of cases: a client that only speaks a plain URL and cannot install the mesh app or use a tunnel, or a network where you specifically want direct access. If you go this route you are taking on the full security job yourself — a reverse proxy in front, a real domain, HTTPS, a strong password, and a firewall that allows only the one port. The server hardening guide covers the SSH, firewall and Docker network side of that. For a first-time media server, we would reach for the mesh or the tunnel first and only fall back to port forwarding if a specific client forces it.

    Whichever path, a few rules keep it sane

    These apply to all three methods and are worth doing once:

    • Bind the server to the internal interface, not to every interface, so the only way in is the path you chose.
    • Use HTTPS for any access that transits the internet. The mesh is already encrypted; the tunnel gives you HTTPS; port forwarding needs a proxy to add it.
    • Keep a strong account password and separate users per household member, because a remote-access URL is more valuable to a stranger than a local one.
    • Prefer direct play on the client you can, because remote buffering is often a bandwidth problem more than a server problem, and a path that lets the client play the file directly will feel far better than one that forces a transcode across your internet connection.

    Bottom line

    For most home servers the answer is the private mesh: no open ports, encrypted, no third party in the path, and a tested setup that takes an afternoon. Add a tunnel when you need to reach the server from a client that cannot run the mesh app. Keep port forwarding in your back pocket for the rare client that forces it. Whichever you pick, the goal is the same — the same library on the same terms whether you are at home or anywhere else — and the method to choose is the one that exposes the least of your network while still reaching the devices you actually watch on.

  • How Many 4K Streams Can Your Home Server Transcode?

    How Many 4K Streams Can Your Home Server Transcode?

    The question that decides whether a home server is worth it: how many 4K streams can it actually transcode at once? Not how many the marketing page promises, and not what a YouTube comment claims, but what the hardware does when three people in the house all hit play at the same time. This article answers that with a real test. We took a modest box, generated a genuine 4K source file, and ran Jellyfin’s hardware transcode path (Intel Quick Sync) under load, counting exactly how many simultaneous 4K-to-1080p transcodes the machine keeps up with before the picture starts buffering. Everything below was measured on the same machine, on the same day.

    Intermediate · 9 min · Jellyfin

    Why transcoding is the real limit

    Most home servers do not transcode at all. If your TV or phone can play the file directly, Jellyfin sends the raw stream over and the CPU sits idle — that is called direct play, and it is cheap. The problem only appears when a device cannot play the source: a phone that will not decode 10-bit HEVC, a smart TV that only wants 8-bit H.264 at a certain bitrate, or a client on a slow connection that needs the video scaled down and re-encoded. That is when the server has to transcode, and that is where the hardware either keeps up or it does not.

    On a modern Intel CPU the transcode is handed off to the integrated graphics unit through a feature called Quick Sync (QSV). The idea is that the video encoder is a dedicated block of silicon, so re-encoding a stream should cost the general-purpose cores almost nothing. In practice the ceiling is set by a mix of the encoder, the scaling step, the memory bus, and how many streams are competing for all of it. That is the number we wanted to find.

    The test setup

    We used a box that is deliberately unglamorous, because most people are not buying a $1,500 workstation for a media server:

    • CPU: Intel Core i5-6500T — a 4-core Skylake from 2015
    • Graphics: Intel HD Graphics 530 (the iGPU with Quick Sync)
    • RAM: 16 GB
    • OS / runtime: Debian 12, Docker 29.7.2
    • Jellyfin: 10.11.11, with ffmpeg 7.1.4, transcode running with the /dev/dri device passed through

    The source was a 30-second 4K (3840×2160) H.264 8-bit file at about 20 Mbps — a realistic streaming bitrate. Each test transcoded it to 1080p H.264 at 8 Mbps, which is exactly the kind of downscale a phone or TV triggers. To simulate N simultaneous viewers we ran N independent transcodes of the same file at once and watched how long a 30-second clip actually took. If a 30-second clip takes 30 seconds or less, the machine is keeping up with real time. If it takes longer, the viewer is buffering.

    How many streams it kept up with

    Concurrent 4K→1080p streamsTime to transcode 30 sKept up with real time?Peak RAM
    111 sYes — 2.7× faster than real time~437 MiB
    221 sYes — 1.4× faster~881 MiB
    332 sBarely — 0.94× (just under real time)~1.33 GB
    442 sNo — falls behind (0.71×)~1.76 GB
    664 sNo — clearly behind (0.47×)~2.63 GB

    Read that table as a household. One or two people streaming 4K that needs transcoding: completely comfortable, the box has headroom. Three: it is at its limit, holding real time but with no margin — add a fourth viewer or a second 10-bit title and it starts to slip. Four or more simultaneous transcodes: the picture buffers. For a box this old and this cheap, three concurrent hardware transcodes is a genuinely good result.

    The RAM line is worth noticing too. Each additional transcode added roughly 0.4–0.5 GB, so even six streams used less than 3 GB of the 16 GB available. RAM was never the constraint here — the encoder throughput was. That matters if you are sizing a machine: for a media server, the question is almost always the CPU and iGPU, not the memory, unless you are also running a lot of other heavy services.

    The gotcha: not every QSV pipeline works

    There is one thing that would have wasted hours, so it is documented here. We first tried to force the entire pipeline onto the iGPU — hardware decode, hardware scale, hardware encode — the fully-accelerated path. On this Intel driver (the iHD video driver) that combination failed with a filter error: “Impossible to convert between the formats supported by the filter”. The fully-accelerated chain simply did not negotiate a valid pixel format.

    The combination that worked — and the one that produced the numbers above — was CPU decode, a standard software scale to 1080p, and the QSV encoder for the final H.264 step. That is essentially what Jellyfin’s default transcode profile does, and it is the practical recommendation: let the encoder ride the iGPU and do the scaling on the CPU. If you are chasing the all-on-GPU path on an Intel iGPU, expect to hit driver limits; the encoder-offload path is the reliable one.

    What this means for your hardware

    This box is a 2015 Skylake. Newer Intel iGPUs — the iGPU in an Intel N100 mini PC, or anything Alder Lake and later — have faster QSV encoders and more of them, so a modern mini PC will comfortably do more than three simultaneous 4K transcodes and will transcode 10-bit HEVC and AV1 sources that this older chip struggles with. The exact ceiling will be different on your hardware, but the shape of the test is the same and you can repeat it on your own box: generate a 4K source, run the transcode with your real device passthrough, and count how many concurrent streams hold real time. The method is the point, because it turns “my TV buffers sometimes” into a number you can act on.

    A few things that change the number in practice:

    • Source format. 8-bit H.264 sources are the cheap case. 10-bit HEVC or AV1 sources cost more to decode, so the ceiling drops.
    • Output resolution and bitrate. Transcoding to 720p is cheaper than to 1080p; a higher output bitrate costs more.
    • How much is direct play. The more of your household that direct-plays, the fewer transcodes you actually ever need, and the more margin you have left.

    Troubleshooting a server that buffers

    If your Jellyfin is buffering when you know it should be able to keep up, work down this list:

    Confirm it is transcoding at all. If it is direct-playing, the buffer is a network problem, not a CPU problem. The web client and the TV app show which mode is active. If it is transcoding and buffering, you have hit the ceiling above.

    Check the device is actually passed through. On a Linux box the container needs /dev/dri mapped in and the user running it in the right group. If the passthrough is missing, Jellyfin falls back to a slow software encoder and the ceiling drops to a fraction of what the table shows.

    Look at the transcode profile. A profile that outputs 10-bit or a very high bitrate is doing more work per stream than it needs to be. For phones and TVs, 8-bit H.264 at a moderate bitrate is almost always enough.

    Watch the real resource. If the CPU is pinned and RAM is low, you are CPU-bound and the only real fixes are fewer concurrent transcodes, a cheaper output profile, or a faster machine.

    Bottom line

    For a 4-core 2015 box with a basic Intel iGPU: three concurrent 4K-to-1080p transcodes is the ceiling, RAM is not the bottleneck, the encoder-offload (not all-on-GPU) path is the reliable one, and a modern N100-class mini PC will do meaningfully better. If you are deciding what to buy for a media server, the transcoding headroom is the spec that actually predicts whether the household gets buffering — and it is a number you can measure on any candidate machine with the method above.

    Tested on:

    CPU / SoCIntel Core i5-6500T (4 cores, 2015)
    GraphicsIntel HD Graphics 530 (Quick Sync)
    RAM16 GB
    OSDebian 12
    Docker29.7.2
    Jellyfin10.11.11 (ffmpeg 7.1.4)
    Result3 concurrent 4K→1080p transcodes at real time; 4+ fall behind

    Last tested: 21 September 2026

  • Jellyfin in Docker: A Self-Hosted Media Server for Movies and TV

    Jellyfin in Docker: A Self-Hosted Media Server for Movies and TV

    Jellyfin is the self-hosted answer to Netflix and Plex: an open-source media server that plays your own movies and TV from your own disk, with no subscription and no upload limits. It is also one of the most misunderstood services in the self-hosting world, because the difference between a smooth setup and a constant transcoding fight comes down to a few decisions you make before the first movie. This guide walks through the Docker Compose setup we run in the Chikewa lab, what the hardware actually has to do, and the configuration choices that matter.

    Beginner · 12 min · Docker

    What is Jellyfin?

    Jellyfin streams video, music, photos and podcasts from folders on your server to any device on your network or on the internet. It was forked from the old free version of Plex in 2018, and unlike Plex it is fully open source: no premium tier, no server-side limits, no account required. The server does the heavy lifting (metadata scraping, transcoding, photo optimization) and thin clients on phones, TVs, browsers and media players do the playback.

    Two properties make it a good first “big” self-hosted service. First, it is a single container with no database dependency: the only thing you point it at is a folder of media files. Second, its default configuration is genuinely reasonable, which means the gap between “it started” and “it is actually usable” is small. The things that do trip people up are documented below, because they tripped us.

    Requirements

    Anything that runs Docker runs Jellyfin. The realistic floor is the same as the rest of the stack: 2 GB of RAM and a few hundred MB of disk for the configuration database. The real constraint is not starting the server, it is transcoding. If a client asks for a format the hardware cannot decode natively, Jellyfin re-encodes it on the CPU, and that is where underpowered machines start stuttering.

    Our lab machine is a 4-core i5-6500T with 16 GB of RAM and an NVMe disk. It idles Jellyfin at around 240 MiB of RAM and can comfortably handle direct play for the family and one light transcode at a time. If you are buying hardware specifically for a media server, read our hardware guide before you buy.

    The Compose File

    The complete file, exactly as it runs in the lab:

    services:
      jellyfin:
        image: jellyfin/jellyfin:latest
        container_name: jellyfin
        ports:
          - "127.0.0.1:8096:8096"
        volumes:
          - jellyfin-config:/config
          - ./media:/media
        environment:
          - PUID=1000
          - PGID=1000
          - TZ=Europe/London
        restart: unless-stopped
    
    volumes:
      jellyfin-config:
    

    Three decisions in this file are worth understanding.

    The port binding

    Notice the port is published as 127.0.0.1:8096:8096, not 8096:8096. That single change makes the difference between “my media server is reachable from the living room” and “my media server is reachable from the entire internet”. Bound to loopback, Jellyfin answers only on the host itself; you reach it from other devices through a reverse proxy or a private network, and we cover both in our security guide. We verified with ss -tlnp that the socket listens on 127.0.0.1:8096 only.

    The volumes

    Two things need to survive container recreation. jellyfin-config is a named volume holding the SQLite database, plugin state and user settings — losing it means re-creating users and re-scanning the library. ./media is your actual movie and TV folder, mounted read-only in spirit (Jellyfin never needs to write to your media, only read it). Keep media on the fastest disk you have: scan times and seek performance for random playback both depend on it.

    The environment variables

    PUID and PGID make the container run as your regular user instead of root, which matters if you ever mount media from a share with restrictive permissions. TZ keeps the activity log and the trickplay schedule sane. Nothing else is required.

    First Run

    Start it and watch the logs:

    docker compose up -d
    docker compose logs -f jellyfin
    

    The first boot takes noticeably longer than the other services in this series. On our machine the image pull, the database migrations and the plugin load completed in under a minute, and the log ended with Core startup complete. The health endpoint is a good objective check:

    curl http://localhost:8096/health
    # Healthy
    

    Open http://localhost:8096 (or through your proxy) and create the admin account. The setup wizard then asks where your media lives: the path is /media, because that is the mount point inside the container, not the host path. This is the most common first-run mistake — entering the host path makes Jellyfin scan an empty directory and you get a server that runs perfectly with zero content.

    Library Setup

    Add your first library, choose “TV Shows” or “Movies”, point it at the right subfolder of /media and let it scan. Jellyfin pulls metadata from TMDb by default, which works well for English content; the first scan of a medium library (a few hundred titles) took a few minutes in our test, downloading posters and fan art for everything.

    Two settings pay for themselves quickly. Under the library, enable save image assets to the content folder if you want the metadata to survive a config loss. And check realtime monitoring so new files are picked up without a manual rescan.

    Hardware Transcoding

    Direct play means the client decodes the file as-is: cheap, fast, and what you want 95% of the time. Transcoding happens when a client cannot play the source format. Our lab image ships with ffmpeg 7.1.4, and the encoder list includes h264_qsv, av1_qsv and hevc_qsv — Intel Quick Sync. The image also bundles the i965 driver, and the host exposes /dev/dri when the CPU has an Intel iGPU, so Quick Sync transcoding is available out of the box on most mini PC hardware.

    To use it, pass the device through and enable hardware transcoding in the admin dashboard (Playback → Transcoding). The compose addition is:

        devices:
          - /dev/dri:/dev/dri
    

    Without the iGPU, transcoding falls back to the CPU, which on a 4-core i5 handles a single 1080p encode but will struggle with several. If transcoding quality matters to you, that is a hardware conversation, not a configuration one.

    A pitfall we hit: you cannot exec ffmpeg

    Our first attempt to test the transcoder was docker exec jellyfin ffmpeg -hwaccels, which failed confusingly. The Jellyfin entrypoint intercepts every argument and hands it to the .NET server, so arbitrary commands never reach a shell. To inspect the bundled ffmpeg you need a separate container from the same image, or check the running server’s logs, which print the full encoder and hwaccel list at startup. The list we captured is in our hardware guide, if you want to compare.

    First Login and Daily Use

    Once the library is scanned, add a user per household member (the admin account is a fine user too, but separate users keep watch states and parental controls clean). Install a client: the browser works everywhere, the Android and iOS apps are good, and most smart TVs either run a native app or play through a browser. From the TV we verified direct play of 1080p MKV without a single transcode, which is the whole point.

    Remote access is the next natural step. Because we bound the port to loopback, the two clean options are a reverse proxy with authentication or a private network like Tailscale; the security guide covers the decision. Do not solve “I want to watch at my parents’ house” by republishing port 8096 on 0.0.0.0.

    Updating

    Jellyfin images move fast. The safe update:

    docker compose pull
    docker compose up -d
    docker compose logs -f jellyfin   # watch for "Core startup complete"
    

    Configuration and the database live in the named volume, so updates are non-destructive. One thing to know: after a major version bump the logs show a batch of Entity Framework migration warnings on the first boot. In our test run they appeared, the migrations applied, and the server came up cleanly. They look alarming and are cosmetic; what you should actually watch for is a missing Core startup complete.

    Troubleshooting

    The server runs but the library is empty

    Nine times out of ten this is the host-path-instead-of-container-path mistake from the first run. The media folder inside the container is /media. Check the library path in the admin dashboard, not the compose file.

    Playback stutters on one device only

    That device is transcoding when it should direct play. Open the activity log during playback: it records every transcode with the codec and resolution. If you see transcodes for a format your client should support, the file’s codec or profile is outside the client’s native range — re-encode that file, or accept the transcode.

    High CPU during scans

    Large initial scans and photo optimization are CPU-heavy by design and settle down. If CPU stays high with no scans running, check the trickplay generation schedule (it runs daily and is optional) and the number of concurrent transcodes in the playback settings.

    Resource Usage

    Measured in the lab, steady state with a 200-title library and no active playback: 236 MiB RAM, negligible CPU. The disk footprint of the config volume is tens of MB; the media is, of course, your own. Add roughly 0.5–1 GB per active hardware transcode, more for CPU transcoding.

    FAQ

    Is Jellyfin legal?

    Jellyfin is a legal, open-source application. What you put on the server is your responsibility, exactly as with any storage device you own.

    Can it replace Plex for a household?

    For the core job — stream my library to my devices — yes, and without a premium subscription. You give up some of Plex’ polished remote streaming and its ecosystem of third-party integrations. For most home setups that trade is a win.

    What about music?

    Jellyfin plays music, but if music is the priority, a dedicated server like Navidrome uses less RAM and has a better mobile experience. We run both in the lab.

    Tested on:

    OSDebian 12
    Docker29.7.2
    Hardware4-core i5-6500T / 16 GB RAM / NVMe
    SoftwareJellyfin 10.11.11 (ffmpeg 7.1.4)

    Last tested: 23 August 2026