obsidian/wiki/claude-code/lmstudio-lms-cli.md

title	aliases	tags	sources	created	updated
lms — LM Studio CLI	lms-cli lmstudio-cli	lmstudio cli local-llm inference server	raw/lms — LM Studio's CLI.md	2026-04-30	2026-04-30

lms — LM Studio CLI

lms is LM Studio's built-in CLI utility for managing models, the inference server, and the runtime. Ships with LM Studio — no separate install needed. MIT licensed, open source on GitHub.

Installation & Verification

# Already installed with LM Studio — just verify:
lms --help

Current version: v0.0.47

Command Reference

Command	What it does
lms chat	Start interactive chat with a model in the terminal
lms get	Search and download models
lms ls	List models available on disk
lms ps	List models currently loaded in memory
lms load	Load a model (with GPU/context options)
lms unload	Unload a model
lms import	Import a model file into LM Studio
lms server start/stop	Control the local API server
lms log	Stream incoming/outgoing messages for debugging
lms runtime	Manage and update the inference runtime
lms daemon	Manage the headless llmster daemon
lms link	Manage LM Link
lms clone	Clone an artifact from LM Studio Hub
lms push	Upload artifact to LM Studio Hub
lms login	Authenticate with LM Studio

Common Workflows

Server control

lms server start
lms server stop

List & inspect models

lms ls        # models on disk (reflects My Models directory)
lms ps        # models currently loaded in memory

Load a model

# With GPU offload and context size:
lms load [--gpu=max|auto|0.0-1.0] [--context-length=1-N]

# --gpu=1.0 → 100% GPU offload
# With a stable identifier alias:
lms load openai/gpt-oss-20b --identifier="my-model-name"

Using --identifier keeps the model ID stable across loads — useful when client code hardcodes a model name.

Unload a model

lms unload           # unload specific model
lms unload --all     # unload everything

Debug message flow

lms log stream       # tail all incoming/outgoing API messages live

Pairs with wiki/claude-code/lmstudio-chat-completions for debugging request/response cycles.

Key Takeaways

• lms ships with LM Studio — zero extra install steps
• lms ps vs lms ls: loaded-in-memory vs on-disk — two different commands
• --gpu=1.0 forces full GPU offload; --gpu=auto lets LM Studio decide
• --identifier flag on lms load decouples client model names from actual model paths
• lms log stream is the fastest way to debug what's hitting the server
• lms daemon manages wiki/claude-code/lmstudio-headless-service for headless/service deployments
• MIT licensed: safe to embed in scripts and automation

Related Articles

• wiki/claude-code/lmstudio-rest-api — all API endpoints
• wiki/claude-code/lmstudio-headless-service — daemon mode for servers
• wiki/claude-code/lmstudio-server-settings — port, auth, CORS, JIT loading
• wiki/claude-code/lmstudio-chat-completions — OpenAI-compat /v1/chat/completions
• wiki/claude-code/lmstudio-llmster-systemd — run llmster at boot on Linux
• wiki/claude-code/lmstudio-idle-ttl-auto-evict — memory management

Sources

• lmstudio.ai/docs/cli