The LinuxServer.io team brings you another container release featuring:

• regular and timely application updates
• easy user mappings (PGID, PUID)
• custom base image with s6 overlay
• weekly base OS updates with common layers across the entire LinuxServer.io ecosystem to minimise space usage, down time and bandwidth
• regular security updates

Find us at:

• Blog - all the things you can do with our containers including How-To guides, opinions and much more!
• Discord - realtime support / chat with the community and the team.
• Discourse - post on our community forum.
• GitHub - view the source for all of our repositories.
• Open Collective - please consider helping us by either donating or contributing to our budget

linuxserver/lm-studio

LM Studio can run local AI models like gpt-oss, Llama, Gemma, Qwen, and DeepSeek privately on your computer.

Supported Architectures

We utilise the docker manifest for multi-platform awareness. More information is available from docker here and our announcement here.

Simply pulling lscr.io/linuxserver/lm-studio:latest should retrieve the correct image for your arch, but you can also pull specific arch images via tags.

The architectures supported by this image are:

Architecture	Available	Tag
x86-64	✅	amd64-<version tag>
arm64	❌

Application Setup

LM Studio can be accessed at:

• https://yourhost:3001/

GPU Support

This image is Arch based and supports the following GPUs:

• Cuda v13- This requires a 2000 series or higher Nvidia video card running the latest binary drivers, v12 is not supported.
• Vulkan- This requires a semi modern AMD GPU.

ROCm is not supported at this time due to it's size and Vulkan option for AMD.

Minimum run commands (start here then expand to fit your needs)

AMD GPUs:

docker run --rm -it \
  --shm-size=1gb \
  --device /dev/dri \
  -e AUTO_GPU=true \
  -p 3001:3001 \
  linuxserver/lm-studio bash

Nvidia GPUs:

As of driver 595.80 with NVIDIA Container Toolkit installed:

# Host level modprobe modeset
nvidia-modprobe --modeset

docker run --rm -it \
  --shm-size=1gb \
  --device /dev/nvidia-modeset \
  --runtime nvidia \
  --gpus all \
  -e AUTO_GPU=true \
  -p 3001:3001 \
  linuxserver/lm-studio bash

AI tools included in this image

This image comes preloaded with a set of AI development and automation tools centered around LM Studio, enabling local model execution, and integration inside a KDE desktop environment.

At the core is LM Studio along with its developer ecosystem via lmstudio SDK, providing programmatic access to local models and workflows.

For AI-assisted coding and agentic workflows, the image includes:

• Aider (via aider-install) for git-aware code editing with LLM assistance (manual configuration required)
• Cline for agent style development inside development environments
• Code-OSS for a desktop IDE with AI plugin support
• OpenClaw for running autonomous AI agents that execute tasks through workflows and messaging based interaction
• OpenCode AI for code generation and refactoring

These tools are primarily CLI and developer focused, and are designed to be configured by the user from the terminal on first launch to connect to a local LM Studio backend.

Included is a desktop launcher for LLMster to provide the backend for these tools in the desktop environment in a headless manner. This can also be launched with lms server start from the command line or from the desktop application via the taskbar icon.

Important notes:

• LM Studio (the desktop application) and LLMster cannot be run at the same time, as they both manage overlapping runtime resources for local model access and will conflict if launched concurrently.
• All included AI tools require initial configuration to point to the active LM Studio backend before use.

Strict reverse proxies

This image uses a self-signed certificate by default. This naturally means the scheme is https. If you are using a reverse proxy which validates certificates, you need to disable this check for the container.

This container is based on Docker Baseimage Selkies, which streams a desktop or single application to your web browser. Only the essentials are covered below, the full platform documentation lives at docs.linuxserver.io/selkies.

Start Minimal

Most support issues we see stem from large run configurations assembled from years of forum posts. These containers are designed to work with almost nothing. Start with the minimal command below, confirm it works, then add your options (volumes, env vars, GPU flags) one at a time:

docker run --rm -it \
  --shm-size=1gb \
  -p 3001:3001 \
  lscr.io/linuxserver/lm-studio:latest bash

Open https://localhost:3001 (note the https) and accept the self signed certificate warning. The trailing bash gives you a shell inside the container, ctrl+d exits and cleans everything up. If a bigger setup misbehaves, return to this command to isolate the problem, see the Quickstart and Troubleshooting guides.

GPU Acceleration

A GPU is optional, the CPU pipeline is fast enough for smooth sessions on modest hardware. When a GPU is mounted into the container it is automatically detected and configured for zero copy rendering and encoding, set AUTO_GPU=false to disable this behavior.

Intel / AMD (open source drivers), one flag is all it takes:

docker run --rm -it \
  --shm-size=1gb \
  -p 3001:3001 \
  --device /dev/dri \
  lscr.io/linuxserver/lm-studio:latest bash

Nvidia (proprietary drivers, not available on Alpine based images):

Requires host driver 580 or newer installed from the .run file downloaded directly from Nvidia. On drivers older than 595.80 you may also need kernel parameters and a dummy plug, see GPU Acceleration before opening an issue.

docker run --rm -it \
  --shm-size=1gb \
  -p 3001:3001 \
  --runtime nvidia \
  --gpus all \
  --device /dev/nvidia-modeset \
  lscr.io/linuxserver/lm-studio:latest bash

Compose examples, multi GPU selection (DRINODE/DRI_NODE), Unraid notes, and a step by step debugging loop are in the GPU Acceleration guide.

Security

Warning

This container provides privileged access to the host system. Do not expose it to the Internet unless you have secured it properly.

HTTPS is required. Modern browser features used for video and audio (WebCodecs) only work in a secure context. Port 3001 serves HTTPS directly, the HTTP port exists only to sit behind a reverse proxy.

By default there is no authentication. Setting the CUSTOM_USER and PASSWORD environment variables enables HTTP basic auth, which is suitable only for a trusted local network. For internet exposure, place the container behind a reverse proxy with robust authentication, such as SWAG. Keep in mind the web interface includes a terminal with passwordless sudo, anyone who can reach the GUI can gain root inside the container.

Authentication options, sharing link behavior, container isolation, and the lockdown variables for kiosk style deployments are covered in Security and Hardening.

Language Support - Internationalization

To launch the session in a different language, set the LC_ALL environment variable, e.g. -e LC_ALL=zh_CN.UTF-8 (Chinese), ja_JP.UTF-8 (Japanese), ko_KR.UTF-8 (Korean), ar_AE.UTF-8 (Arabic), ru_RU.UTF-8 (Russian), es_MX.UTF-8 (Spanish Latin America), de_DE.UTF-8 (German), fr_FR.UTF-8 (French), nl_NL.UTF-8 (Dutch), it_IT.UTF-8 (Italian).

Beyond Running the App

This image inherits every capability of the Selkies platform, all documented in depth on the docs site:

• Configuration Reference - every environment variable: ports, subfolder reverse proxy, custom dashboards, watermarking, and the full set of SELKIES_* stream, feature, and UI settings with their |locked syntax.
• Using the Web Client - file transfer, clipboard sync, audio and microphone, up to four gamepads, session sharing, and mobile touch support.
• Installing Applications - persistent user installed apps with proot-apps (proot-apps install filezilla) or native packages at boot with Docker mods.
• Docker in Docker and host Docker control - run --privileged for an isolated DinD setup, or mount /var/run/docker.sock to manage the host.
• Reverse Proxy - proxying websockets and subfolders correctly.
• SealSkin - turnkey multi user VDI orchestration with browser extension and mobile apps, this image is fully compatible.
• Pelorus - expose the session to AI agents via a computer use API and accessibility stack.

Usage

To help you get started creating a container from this image you can either use docker-compose or the docker cli.

Note

Unless a parameter is flagged as 'optional', it is mandatory and a value must be provided.

docker-compose (recommended, click here for more info)

---
services:
  lm-studio:
    image: lscr.io/linuxserver/lm-studio:latest
    container_name: lm-studio
    environment:
      - PUID=1000
      - PGID=1000
      - TZ=Etc/UTC
    volumes:
      - /path/to/config:/config
    ports:
      - 3000:3000
      - 3001:3001
    shm_size: "1gb" #optional
    restart: unless-stopped

docker cli (click here for more info)

docker run -d \
  --name=lm-studio \
  -e PUID=1000 \
  -e PGID=1000 \
  -e TZ=Etc/UTC \
  -p 3000:3000 \
  -p 3001:3001 \
  -v /path/to/config:/config \
  --shm-size="1gb" `#optional` \
  --restart unless-stopped \
  lscr.io/linuxserver/lm-studio:latest

Parameters

Containers are configured using parameters passed at runtime (such as those above). These parameters are separated by a colon and indicate <external>:<internal> respectively. For example, -p 8080:80 would expose port 80 from inside the container to be accessible from the host's IP on port 8080 outside the container.

Parameter	Function
-p 3000:3000	LM Studio desktop gui HTTP, must be proxied.
-p 3001:3001	LM Studio desktop gui HTTPS.
-e PUID=1000	for UserID - see below for explanation
-e PGID=1000	for GroupID - see below for explanation
-e TZ=Etc/UTC	specify a timezone to use, see this list.
-v /config	Users home directory in the container, stores program settings and files.
--shm-size=	Required for the desktop enrionment to function.

Environment variables from files (Docker secrets)

You can set any environment variable from a file by using a special prepend FILE__.

As an example:

-e FILE__MYVAR=/run/secrets/mysecretvariable

Will set the environment variable MYVAR based on the contents of the /run/secrets/mysecretvariable file.

Umask for running applications

For all of our images we provide the ability to override the default umask settings for services started within the containers using the optional -e UMASK=022 setting. Keep in mind umask is not chmod it subtracts from permissions based on it's value it does not add. Please read up here before asking for support.

User / Group Identifiers

When using volumes (-v flags), permissions issues can arise between the host OS and the container, we avoid this issue by allowing you to specify the user PUID and group PGID.

Ensure any volume directories on the host are owned by the same user you specify and any permissions issues will vanish like magic.

In this instance PUID=1000 and PGID=1000, to find yours use id your_user as below:

id your_user

Example output:

uid=1000(your_user) gid=1000(your_user) groups=1000(your_user)

Docker Mods

We publish various Docker Mods to enable additional functionality within the containers. The list of Mods available for this image (if any) as well as universal mods that can be applied to any one of our images can be accessed via the dynamic badges above.

Support Info

• Shell access whilst the container is running:

  docker exec -it lm-studio /bin/bash

• To monitor the logs of the container in realtime:

  docker logs -f lm-studio

• Container version number:

  docker inspect -f '{{ index .Config.Labels "build_version" }}' lm-studio

• Image version number:

  docker inspect -f '{{ index .Config.Labels "build_version" }}' lscr.io/linuxserver/lm-studio:latest

Updating Info

Most of our images are static, versioned, and require an image update and container recreation to update the app inside. With some exceptions (noted in the relevant readme.md), we do not recommend or support updating apps inside the container. Please consult the Application Setup section above to see if it is recommended for the image.

Below are the instructions for updating containers:

Via Docker Compose

• Update images:

  • All images:

    docker-compose pull

  • Single image:

    docker-compose pull lm-studio

• Update containers:

  • All containers:

    docker-compose up -d

  • Single container:

    docker-compose up -d lm-studio

• You can also remove the old dangling images:

  docker image prune

Via Docker Run

• Update the image:

  docker pull lscr.io/linuxserver/lm-studio:latest

• Stop the running container:

  docker stop lm-studio

• Delete the container:

  docker rm lm-studio

• Recreate a new container with the same docker run parameters as instructed above (if mapped correctly to a host folder, your /config folder and settings will be preserved)

• You can also remove the old dangling images:

  docker image prune

Image Update Notifications - Diun (Docker Image Update Notifier)

Tip

We recommend Diun for update notifications. Other tools that automatically update containers unattended are not recommended or supported.

Building locally

If you want to make local modifications to these images for development purposes or just to customize the logic:

git clone https://github.com/linuxserver/docker-lm-studio.git
cd docker-lm-studio
docker build \
  --no-cache \
  --pull \
  -t lscr.io/linuxserver/lm-studio:latest .

The ARM variants can be built on x86_64 hardware and vice versa using lscr.io/linuxserver/qemu-static

docker run --rm --privileged lscr.io/linuxserver/qemu-static --reset

Once registered you can define the dockerfile to use with -f Dockerfile.aarch64.

Versions

• 22.06.26: - Initial release.