LM Studio, llmster, and lms

LM Studio app, llmster, and lms

The LM Studio app, llmster, and lms are three different tools offered by LM Studio to make use of local AI easy and accessible.

LM Studio (the desktop app)

The LM Studio app is a user-friendly graphical interface containing the full capabilities of LM Studio.

Notable capabilities:

Search and download models from Hugging Face
Chat with models through a built-in chat interface
Upload and chat documents (RAG)
Configure model settings, prompt templates, and presets
Run a local server with through native REST APIs or OpenAI/Anthropic compatible endpoints
Connect MCP servers and use them with local models

The desktop app is the easiest starting point if you're new to running models locally or prefer a graphical interface.

llmster (the headless daemon)

llmster is LM Studio’s headless daemon – a standalone background service that can run without a GUI. This means you do not have to download the LM Studio app to use llmster via the terminal.

llmster becomes useful when you need to run LM Studio:

On a Linux server or cloud instance
On a GPU rig without a screen or display
In a CI/CD pipeline
As a background service that starts on machine boot And more!

Because llmster runs independently of the desktop app, you can get the full model-serving capabilities of LM Studio in environments where installing or launching a GUI application isn't practical.

Learn more and install llmster here

lms (the CLI)

lms is LM Studio's CLI (command-line interface). It lets you interact with both the LM Studio desktop app and llmster, and manage your models directly from a terminal.

lms is included automatically upon downloading the app or llmster.

Common commands:

lms get <model>        # Download a model
lms load <model>       # Load a model into memory
lms ls                 # List models available on disk
lms server start       # Start the local HTTP server
lms chat               # Start an interactive chat session in the terminal
lms log stream         # Stream incoming and outgoing request logs

If LM Studio isn't already running when you run an lms command, it will start running automatically.

Example commands to download and serve a model:

lms get openai/gpt-oss-20b
lms load openai/gpt-oss-20b
lms server start

Once the server is running, it listens on http://localhost:1234. Point any SDK or compatible tool at our OpenAI or Anthropic-compatible endpoints to use your LM Studio models.

In short, lms is the command-line tool to talk to both, the desktop app or llmster.