LM Studio is a free desktop application that lets developers download, run, and interact with open‑source large language models locally on their own hardware. It offers a chat‑style UI and an OpenAI‑compatible API, plus a headless daemon (llmster) for server or CI deployments, and LM Link for secure, encrypted access to remote models as if they were local.
Funding
$19.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Running large language models typically requires cloud services or specialized infrastructure, leading to high costs, data privacy concerns, and latency. Users also lack flexible tools to manage, deploy, and interact with these models on personal or on‑premise hardware.
Solution
LM Studio is a free desktop application that enables users to download, run, and interact with a wide range of open‑source LLMs directly on their own computers. It provides a chat‑style UI as well as a programmable API compatible with OpenAI, Anthropic, and custom endpoints, allowing seamless integration into existing workflows. For server or CI environments, the headless daemon llmster offers the same runtime without a graphical interface, installable via a single script on macOS, Linux, or Windows. LM Link extends the platform by securely linking multiple devices—local machines, on‑premise servers, or cloud VMs—through end‑to‑end encrypted Tailscale mesh VPNs, making remote models appear as local resources. The platform continuously updates model catalogs, supports multimodal inputs, tool calling, and advanced features such as parallel batching and custom reasoning controls, all while keeping data on the user’s hardware.
Target Audience
Primary users are software developers, data scientists, and enterprise AI teams that need on‑premise LLM inference for privacy‑sensitive or latency‑critical applications.
Features
- Graphical chat client with OpenAI‑compatible `/v1/chat/completions`, `/v1/responses`, and Anthropic `/v1/messages` endpoints
- Headless llmster daemon for server, cloud, or CI deployments, installable via one‑line script
- Integrated model hub offering dozens of open‑source LLMs (e.g., Gemma 4, Qwen 3.6, Nemotron 3 series) with automatic resource estimation and quantization support
- LM Link: end‑to‑end encrypted device mesh using Tailscale VPN, enabling remote model execution as if local
- Built‑in tool‑calling, multimodal (vision/audio) handling, and configurable reasoning effort parameters
- Parallel request handling and continuous batching for low‑latency inference on GPU/CPU
- Extensible JavaScript, Python, and CLI SDKs for custom application development