108 lines
3.5 KiB
Markdown
108 lines
3.5 KiB
Markdown
---
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title: "lms — LM Studio CLI"
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aliases: [lms-cli, lmstudio-cli]
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tags: [lmstudio, cli, local-llm, inference, server]
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sources: [raw/lms — LM Studio's CLI.md]
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created: 2026-04-30
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updated: 2026-04-30
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---
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# lms — LM Studio CLI
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`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.
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## Installation & Verification
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```bash
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# Already installed with LM Studio — just verify:
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lms --help
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```
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Current version: `v0.0.47`
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## Command Reference
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| Command | What it does |
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|---------|-------------|
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| `lms chat` | Start interactive chat with a model in the terminal |
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| `lms get` | Search and download models |
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| `lms ls` | List models available on disk |
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| `lms ps` | List models currently loaded in memory |
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| `lms load` | Load a model (with GPU/context options) |
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| `lms unload` | Unload a model |
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| `lms import` | Import a model file into LM Studio |
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| `lms server start/stop` | Control the local API server |
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| `lms log` | Stream incoming/outgoing messages for debugging |
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| `lms runtime` | Manage and update the inference runtime |
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| `lms daemon` | Manage the headless llmster daemon |
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| `lms link` | Manage LM Link |
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| `lms clone` | Clone an artifact from LM Studio Hub |
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| `lms push` | Upload artifact to LM Studio Hub |
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| `lms login` | Authenticate with LM Studio |
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## Common Workflows
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### Server control
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```bash
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lms server start
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lms server stop
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```
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### List & inspect models
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```bash
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lms ls # models on disk (reflects My Models directory)
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lms ps # models currently loaded in memory
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```
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### Load a model
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```bash
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# With GPU offload and context size:
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lms load [--gpu=max|auto|0.0-1.0] [--context-length=1-N]
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# --gpu=1.0 → 100% GPU offload
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# With a stable identifier alias:
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lms load openai/gpt-oss-20b --identifier="my-model-name"
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```
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Using `--identifier` keeps the model ID stable across loads — useful when client code hardcodes a model name.
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### Unload a model
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```bash
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lms unload # unload specific model
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lms unload --all # unload everything
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```
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### Debug message flow
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```bash
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lms log stream # tail all incoming/outgoing API messages live
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```
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Pairs with [[wiki/claude-code/lmstudio-chat-completions|lmstudio-chat-completions]] for debugging request/response cycles.
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## Key Takeaways
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- `lms` ships with LM Studio — zero extra install steps
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- `lms ps` vs `lms ls`: loaded-in-memory vs on-disk — two different commands
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- `--gpu=1.0` forces full GPU offload; `--gpu=auto` lets LM Studio decide
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- `--identifier` flag on `lms load` decouples client model names from actual model paths
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- `lms log stream` is the fastest way to debug what's hitting the server
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- `lms daemon` manages [[wiki/claude-code/lmstudio-headless-service|llmster]] for headless/service deployments
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- MIT licensed: safe to embed in scripts and automation
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## Related Articles
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- [[wiki/claude-code/lmstudio-rest-api|LM Studio REST API]] — all API endpoints
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- [[wiki/claude-code/lmstudio-headless-service|Headless Service (llmster)]] — daemon mode for servers
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- [[wiki/claude-code/lmstudio-server-settings|Server Settings]] — port, auth, CORS, JIT loading
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- [[wiki/claude-code/lmstudio-chat-completions|Chat Completions]] — OpenAI-compat `/v1/chat/completions`
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- [[wiki/claude-code/lmstudio-llmster-systemd|llmster systemd unit]] — run llmster at boot on Linux
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- [[wiki/claude-code/lmstudio-idle-ttl-auto-evict|Idle TTL & Auto-Evict]] — memory management
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## Sources
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- lmstudio.ai/docs/cli
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