In this video, I walk step by step through how to install LM Studio on Ubuntu ARM64 and how to set up the headless LM Studio daemon / LLM server on an NVIDIA DGX Spark. Installing LM Studio on Windows is simple, but on Linux and ARM64 hardware the process is much more manual. I show both approaches: the GUI desktop installation for workstation use and the headless setup for running your DGX Spark as a dedicated local LLM server.
Contents:
0:00 - Introduction
0:15 - Description
1:27 - LM Studio Install
8:19 - DGX differences
9:27 - Desktop Version Problem
11:10 - llmster
14:21 - Lms Service
17:57 - Lms Upgrade
18:42 - LM Studio Upgrade
19:38 - Conclusion
You’ll see how to download the correct ARM64 AppImage, extract it manually, fix the Chrome sandbox permissions, create a working desktop launcher, and configure autostart on Ubuntu. Then I switch to the headless route and demonstrate how to install the LM Studio daemon, use the LMS command line, download and run models, expose the API on port 1234, and configure a systemd user service so the server starts automatically even without a logged-in session.
I also cover practical differences between Windows and Linux, unified memory behavior on the DGX Spark, CUDA detection, remote model access through LM Studio remote, and how to update the daemon cleanly when new versions are released.
If you want to run local LLMs on Ubuntu, ARM64, or NVIDIA DGX Spark, this tutorial will save you time and help you avoid the small issues that usually appear during installation.
What you’ll learn:
LM Studio install on Ubuntu ARM64
DGX Spark local LLM setup
LM Studio GUI vs headless daemon
AppImage extraction and permissions
Chrome sandbox fix
Desktop icon and autostart on Ubuntu
LMS command-line usage
systemd service configuration
API server on port 12341234
Remote access to local models
Upgrade LM Studio
If this video helps, please like, subscribe, and leave a comment with your DGX Spark or Ubuntu LLM setup.
#LMStudio #DGXSpark #LocalLLM
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