Create agents with MCP tools, skills, memory, RAG, citations, and streamed execution from the UI or API.
+++ title = "LocalAI" description = "The open, modular AI runtime. Run text, vision, voice, image, video, agents, and more on hardware you control." type = "home" +++
Open source · MIT licensed
LocalAI runs text, vision, speech, sound, images, video, embeddings, reranking, and autonomous agents behind one modular stack—from a CPU laptop to a distributed GPU cluster.
The runtime, not just the endpoint.
A small core, not a giant bundle.
LocalAI keeps the core lean. Each backend wraps a best-in-class engine—llama.cpp, vLLM, SGLang, MLX, whisper.cpp, diffusion engines, and many more—as an isolated service pulled on demand.

We integrate the best engines. We build new ones, too.
The LocalAI team develops native C, C++, Rust, and GGML engines when the available stack is too heavy, too closed, or simply does not exist yet.
See the engines we maintain ↗Start on one machine. Keep going.
Run useful models locally, including CPU-only setups.
Add authentication, API keys, roles, quotas, and usage visibility.
Route across workers, fit models across devices, and scale with demand.
More than inference
Create agents with MCP tools, skills, memory, RAG, citations, and streamed execution from the UI or API.
Build interruptible voice experiences with WebRTC, streaming STT, LLM output, and TTS.
Keep data on your infrastructure and add PII analysis, redaction, policy middleware, and audit visibility.
Discover capabilities, import models, fine-tune, quantize, route, and monitor them in one place.
One command to begin
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest