LM Studio is a free desktop app to run local LLMs on your own computer

LM Studio is a free desktop app that runs local large language models on macOS, Windows, and Linux, offering a private, offline alternative to cloud chatbots. The app downloads open models including gpt-oss, Llama, Qwen, DeepSeek R1, Mistral, and Gemma from Hugging Face, and serves OpenAI-compatible endpoints at localhost:1234 plus an Anthropic-compatible Messages API for Claude Code. LM Studio recommends 16GB+ RAM on Apple Silicon Macs running macOS 14.0+ and 16GB RAM with 4GB+ VRAM on x64/ARM64 Windows 10/11 and Ubuntu 20.04+ Linux systems, and also ships Python and TypeScript SDKs and the MIT-licensed lms CLI.

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.