LocalAI
Open-source AI engine, run any model locally
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Oct 2026
LocalAI is a self-hosted stand-in for the OpenAI API. It runs text, vision, speech, image and video models on your own hardware, CPU-only if that's all you have, and answers on OpenAI, Anthropic, Ollama and ElevenLabs-compatible endpoints, so most apps only need a new URL. MIT-licensed and free.
One docker run or the macOS app gets it going. The core stays small: each engine (llama.cpp, vLLM, whisper.cpp, MLX and more) is pulled as a separate backend only when a model needs it, and models install from a gallery, Hugging Face or the Ollama registry. It's well past a hobby server now: API keys, OIDC logins, per-user quotas and a distributed mode that spreads models across GPU machines.
There's no paid tier; hardware is the bill. Solo: free, though Ollama is simpler for one laptop. Small and larger teams: free, and the quotas and cluster mode make it a real internal AI gateway.
The catch: out of the box there's no login. Unless you set an API key or turn on user auth, anyone who can reach the port can use it. A critical unauthenticated SSRF bug was patched in July. Set LOCALAI_API_KEY, stay current, and never expose it raw.
Free vs Self-Hosted vs Paid
fully freeFree: Everything, under MIT. Text, vision, speech-to-text, text-to-speech, image, video and 3D generation, built-in agents with MCP and RAG, multi-user auth with API keys or OIDC, per-user quotas and distributed mode all ship in the open source build.
Self-hosted: The only way to run it: Docker images for CPU, NVIDIA CUDA 12/13, AMD ROCm, Intel oneAPI, Vulkan and Jetson, or an unsigned macOS DMG. Backends download on demand when a model needs them. Your cost is hardware: CPU-only works for small models, a GPU makes larger models practical. Authentication is off unless you configure LOCALAI_API_KEY or LOCALAI_AUTH=true.
Paid: No paid tier and no hosted offering. The project takes GitHub Sponsors and lists a business contact (contact@localai.io), with no published support plans or prices.
Free with no paid tier. Hardware is the only cost, and auth is off until you configure it.
What to do by team size
- Solo
- free; Ollama is simpler if you only need chat models on one laptop
- Small team
- free; set an API key before anyone else can reach it
- Medium team
- free; per-user API keys and quotas make it a shared internal endpoint
- Large team
- free; distributed mode routes across GPU nodes, but you run and secure the cluster yourself
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