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LM Studio

Desktop app to discover, download and run LLMs locally on your own computer (Windows, macOS, Linux) — offline, with an OpenAI-compatible local server.

Producer:Element LabsOn-Premises · Edge
LM Studio
Supported models
11SLM/LLM
SDK / Languages
2python, typescript
Robotics-Ready
✓

Description

What is LM Studio

LM Studio is a desktop application for discovering, downloading and running large language models (LLMs) entirely locally, on your own computer. It runs on Windows (x64/ARM64), macOS (Apple Silicon) and Linux (x64) and lets you use open-weight models such as Llama, Qwen, Gemma, Phi, Mistral, DeepSeek and gpt-oss without sending any data to the cloud.

Inference engines and model formats

The app is built on two engines running under the hood: llama.cpp (for GGUF-format models, on all platforms) and Apple MLX (for MLX-format models on Apple Silicon Macs). It supports quantised models, which makes it possible to run large models on consumer hardware.

Key features

LM Studio provides a graphical chat interface, built-in model search and download (powered by Hugging Face), offline chat with documents (RAG), a local server that exposes models through an OpenAI-compatible API (locally and over the network), tool use (function calling), structured output, and Model Context Protocol (MCP) server support. Official SDKs for Python and TypeScript and the "lms" command-line tool are also available.

Licensing

LM Studio is free — on 8 July 2025 its makers announced that using the app at work no longer requires a commercial license. It is developed by Element Labs, Inc.

Data & KnowledgeData & Knowledge ManagementData connectors, vector database integration, native vector search and data management (PII, provenance, synthetic data).

ApplicationsAI ApplicationsDomains and use cases this platform is best suited for — from RAG and fine-tuning to scientific research.

5

Developer EcosystemDeveloper EcosystemDeveloper resources: available SDKs, supported programming languages, and infrastructure features and model-deployment methods.

SDK Languages
PyPythonTSTypeScript
API Type
REST
Community & resources
Templates library
Quickstarts
API Reference
Tutorials

Supported AI Models

11

SourcesDocumentation VaultCentralized hub of links to official sources, technical guides, repositories and release notes.

Data verified: Sep 29, 2026