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How to use LocalAI: what you can do with it

What is LocalAI? LocalAI is an open-source AI engine that runs LLMs, vision, voice, image and video models on any hardware, with no GPU required. Each backend (llama.cpp, vLLM, whisper.cpp, stable-diffusion, MLX and more) is pulled only when a model needs it, and every backend sits behind drop-in OpenAI, Anthropic and ElevenLabs compatible APIs, with multi-user auth, quotas and built-in agents with tools, RAG and MCP.

How do I use it? Start the CPU image: docker run -ti --name local-ai -p 8080:8080 localai/localai:latest; then Or with an NVIDIA GPU: docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12; load a model, for example local-ai run llama-3.2-1b-instruct:q4_k_m. Full steps below.

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What do you want to do?

3 use cases

Quick start with LocalAI

  1. Check you have what it needs: Docker or Podman, or the macOS app (not signed by Apple); Optional GPU: NVIDIA, AMD, Intel, Apple Silicon or Vulkan; CPU-only works; Disk space for the models you pull.
  2. Open mudler/LocalAI on GitHub and read the README and license.
  3. Start the CPU image: docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
  4. Or with an NVIDIA GPU: docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
  5. Load a model, for example local-ai run llama-3.2-1b-instruct:q4_k_m
  6. Point your app's OpenAI base URL at http://localhost:8080

These steps come from our top use case, Self-host an OpenAI-compatible API on your own server, which also has a copy-paste agent prompt.

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LocalAI alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forDevelopers and teams who want a private, self-hosted replacement for cloud AI APIs that existing OpenAI or Anthropic clients can talk to.
  • Why it is hot50k stars, picked up by one AI source we track
  • LanguageGo
  • Sourcegithub.com/mudler/LocalAI · Back to Hot repos

Requirements

  • Docker or Podman, or the macOS app (not signed by Apple)
  • Optional GPU: NVIDIA, AMD, Intel, Apple Silicon or Vulkan; CPU-only works
  • Disk space for the models you pull

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Questions about LocalAI

What is LocalAI?

LocalAI is an open-source AI engine that runs LLMs, vision, voice, image and video models on any hardware, with no GPU required. Each backend (llama.cpp, vLLM, whisper.cpp, stable-diffusion, MLX and more) is pulled only when a model needs it, and every backend sits behind drop-in OpenAI, Anthropic and ElevenLabs compatible APIs, with multi-user auth, quotas and built-in agents with tools, RAG and MCP. It is an open-source project on GitHub: https://github.com/mudler/LocalAI.

How do I use LocalAI?

Start the CPU image: docker run -ti --name local-ai -p 8080:8080 localai/localai:latest; then Or with an NVIDIA GPU: docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12; load a model, for example local-ai run llama-3.2-1b-instruct:q4_k_m. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is LocalAI for?

Developers and teams who want a private, self-hosted replacement for cloud AI APIs that existing OpenAI or Anthropic clients can talk to.

What can I do with LocalAI?

3 use cases so far, for example: Self-host an OpenAI-compatible API on your own server; Chat with local models from the terminal; Run any model from Hugging Face, Ollama or an OCI registry. Each has steps and a copy-paste agent prompt.

What do I need to run LocalAI?

Docker or Podman, or the macOS app (not signed by Apple); Optional GPU: NVIDIA, AMD, Intel, Apple Silicon or Vulkan; CPU-only works; Disk space for the models you pull.

What are alternatives to LocalAI?

Other hot AI repos in Software and DevOps: Deep Infer, Harness2, Orca, Opencode, Graphify.

Is LocalAI safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.