# LM Studio is a free desktop app to run local LLMs on your own computer > Source: > Published: 2026-09-21 13:02:36+00:00 # Welcome to the LM Studio docs LM Studio is a free desktop app to **run local LLMs on your own computer** — a private, offline **ChatGPT alternative** for macOS, Windows, and Linux. Download open models like gpt-oss, Llama, Qwen, DeepSeek R1, Mistral and Gemma from Hugging Face, chat with your documents, and serve an **OpenAI-compatible local API**. To get started, head over to the [Downloads page](https://lmstudio.ai/download) and grab the installer for your operating system. ## Get started with LM Studio ## System requirements LM Studio generally supports Apple Silicon Macs, x64/ARM64 Windows PCs, and x64 Linux PCs. | Platform | Chip / CPU | OS | Memory | |---|---|---|---| | macOS | Apple Silicon (M1/M2/M3/M4) — Intel Macs are not supported | macOS 14.0+ | 16GB+ RAM recommended | | Windows | x64 (AVX2 required) or ARM (Snapdragon X Elite) | Windows 10/11 | 16GB RAM · 4GB+ VRAM recommended | | Linux | x64 (AVX2) or ARM64 (aarch64) | Ubuntu 20.04+ · AppImage | 16GB RAM · 4GB+ VRAM recommended | ## What can I do with LM Studio? 1. **Download and run local LLMs** like`gpt-oss` ,`Llama` ,`Qwen` ,`Mistral` or`DeepSeek R1` — private AI on your own hardware, no cloud account needed 2. Use a **simple and flexible chat interface** — a private AI chatbot with system prompts, presets and streaming replies 3. **Connect MCP servers** and use tools with local models — files, browsers, and your own automations 4. **Search & download models via Hugging Face** 🤗 — GGUF and MLX weights, managed in one library 5. **Serve local models on OpenAI-like endpoints** , locally and on the network — plus an Anthropic-compatible Messages API for Claude Code 6. **Manage your local models, prompts, and configurations** — GPU offload, context length, and per-model presets ## Popular use cases Why people run LLMs locally with LM Studio instead of renting a cloud chatbot. ## Run llama.cpp (GGUF) or MLX models LM Studio supports running LLMs on Mac, Windows, and Linux using `llama.cpp`. On Apple Silicon Macs, LM Studio also supports running LLMs using Apple’s **MLX** framework. To install or manage LM Runtimes, press `⌘ Shift R` on Mac or `Ctrl Shift R` on Windows/Linux. ## Run an LLM like gpt-oss, Llama, Qwen, Mistral, or DeepSeek R1 on your computer To run an LLM on your computer you first need to download the model weights. You can do this right within LM Studio — open the Discover tab, search Hugging Face, and pick a size your machine can hold. ``` # …or from the terminal lms get qwen3 lms load openai/gpt-oss-20b --gpu=max lms chat ``` ## Offline operation LM Studio can operate entirely offline — just make sure to get some model files first. Chats, inference, and local APIs stay on your machine. ## Developer — local REST API LM Studio provides a REST API that you can use to interact with local models from your own apps and scripts. Serve OpenAI-compatible endpoints (`/v1/chat/completions`, responses, embeddings) and an Anthropic-compatible Messages API — locally or on your network. ``` lms server start curl http://localhost:1234/v1/models ``` For servers, cloud instances, and CI, install **llmster** — LM Studio's headless daemon, no desktop app required: ``` curl -fsSL https://lmstudio.ai/install.sh | bash # macOS / Linux irm https://lmstudio.ai/install.ps1 | iex # Windows ``` ## Python SDK Use `lmstudio-python` to load models, generate text, embed content, and build agents from scripts, notebooks, and backend services. ``` pip install lmstudio ``` ## TypeScript SDK Use `lmstudio-js` to build apps, tools, and local AI workflows in Node.js or TypeScript — including plugins. ``` npm install @lmstudio/sdk ``` ## CLI — `lms` `lms` ships with LM Studio, so no extra install is needed. It is MIT licensed and developed in the open on GitHub. Bootstrap it once, then automate your local LLM workflows. ``` # Bootstrap on macOS / Linux ~/.lmstudio/bin/lms bootstrap # Bootstrap on Windows cmd /c %USERPROFILE%/.lmstudio/bin/lms.exe bootstrap ``` | Command | What it does | |---|---| | `lms chat` | Chat with a model interactively in the terminal | | `lms get` | Search and download models | | `lms ls` | List models on disk (mirrors the My Models tab) | | `lms ps` | List models currently loaded in memory | | `lms load` | Load a model — options like `--gpu=max` ,`--context-length` ,`--identifier` | | `lms unload` | Unload a model ( `--all` for everything) | | `lms server start` | Control the local server | | `lms runtime` | Manage and update inference runtimes | | `lms daemon` | Manage the headless background daemon | | `lms link` | Manage LM Link across devices | ## Bionic Bionic is LM Studio’s agent for open models — natively local, built for creativity, work, and code. It excels at documents, coding tasks, automations, and real-time voice transcription, all processed on-device. For demanding tasks, run Bionic with frontier open models in a Zero Data Retention cloud. ## Integrations Connect LM Studio to the tools you already use. With the Anthropic-compatible `/v1/messages` endpoint, Claude Code can run on your local models with a single base-URL change: ``` export ANTHROPIC_BASE_URL=http://localhost:1234 export ANTHROPIC_AUTH_TOKEN=lmstudio claude # now running on your local model ``` Also works with Codex, VS Code, MCP tools, and any OpenAI-compatible client. ## LM Link LM Link securely connects models across your devices — route local AI workloads to preferred machines and use remote models from another device as if they were local. ## Changelog Current release: **0.4.23**. Highlights of the 0.4.x line include the Anthropic-compatible Messages API, llmster headless daemon, and LM Link. Beta and experimental builds are published on the beta-releases page. ## Frequently asked questions `lms get` and `lms chat` from the terminal. No cloud account needed.