LocalAI is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that's compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by Ettore Di Giacinto.

Local Stack Family

Liking LocalAI? LocalAI is part of an integrated suite of AI infrastructure tools, you might also like:

• LocalAGI - AI agent orchestration platform with OpenAI Responses API compatibility and advanced agentic capabilities
• LocalRecall - MCP/REST API knowledge base system providing persistent memory and storage for AI agents
• 🆕 Cogito - Go library for building intelligent, co-operative agentic software and LLM-powered workflows, focusing on improving results for small, open source language models that scales to any LLM. Powers LocalAGI and LocalAI MCP/Agentic capabilities
• 🆕 Wiz - Terminal-based AI agent accessible via Ctrl+Space keybinding. Portable, local-LLM friendly shell assistant with TUI/CLI modes, tool execution with approval, MCP protocol support, and multi-shell compatibility (zsh, bash, fish)
• 🆕 SkillServer - Simple, centralized skills database for AI agents via MCP. Manages skills as Markdown files with MCP server integration, web UI for editing, Git synchronization, and full-text search capabilities

Screenshots / Video

Youtube video

Screenshots

Talk Interface	Generate Audio

Models Overview	Generate Images

Chat Interface	Home

Login	Swarm

💻 Quickstart

macOS Download:

Note: the DMGs are not signed by Apple as quarantined. See https://github.com/mudler/LocalAI/issues/6268 for a workaround, fix is tracked here: https://github.com/mudler/LocalAI/issues/6244

Containers (Docker, podman, ...)

💡 Docker Run vs Docker Start
> - docker run creates and starts a new container. If a container with the same name already exists, this command will fail.
- docker start starts an existing container that was previously created with docker run.
> If you've already run LocalAI before and want to start it again, use: docker start -i local-ai

CPU only image:

docker run -ti --name local-ai -p 8080:8080 localai/localai:latest

NVIDIA GPU Images:

# CUDA 13.0
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-13

# CUDA 12.0
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12

# NVIDIA Jetson (L4T) ARM64
# CUDA 12 (for Nvidia AGX Orin and similar platforms)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64

# CUDA 13 (for Nvidia DGX Spark)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13

AMD GPU Images (ROCm):

docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas

Intel GPU Images (oneAPI):

docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel

Vulkan GPU Images:

docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan

AIO Images (pre-downloaded models):

# CPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu

# NVIDIA CUDA 13 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-13

# NVIDIA CUDA 12 version
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12

# Intel GPU version
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-gpu-intel

# AMD GPU version
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-aio-gpu-hipblas

For more information about the AIO images and pre-downloaded models, see Container Documentation.

To load models:

# From the model gallery (see available models with `local-ai models list`, in the WebUI from the model tab, or visiting https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# Start LocalAI with the phi-2 model directly from huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# Install and run a model from the Ollama OCI registry
local-ai run ollama://gemma:2b
# Run a model from a configuration file
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# Install and run a model from a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest

⚡ Automatic Backend Detection: When you install models from the gallery or YAML files, LocalAI automatically detects your system's GPU capabilities (NVIDIA, AMD, Intel) and downloads the appropriate backend. For advanced configuration options, see GPU Acceleration.

For more information, see 💻 Getting started, if you are interested in our roadmap items and future enhancements, you can see the Issues labeled as Roadmap here

📰 Latest project news

• February 2026: Realtime API for audio-to-audio with tool calling, ACE-Step 1.5 support
• January 2026: LocalAI 3.10.0 - Major release with Anthropic API support, Open Responses API for stateful agents, video & image generation suite (LTX-2), unified GPU backends, tool streaming & XML parsing, system-aware backend gallery, crash fixes for AVX-only CPUs and AMD VRAM reporting, request tracing, and new backends: Moonshine (ultra-fast transcription), Pocket-TTS (lightweight TTS). Vulkan arm64 builds now available. Release notes.
• December 2025: Dynamic Memory Resource reclaimer, Automatic fitting of models to multiple GPUS(llama.cpp), Added Vibevoice backend
• November 2025: Major improvements to the UX. Among these: Import models via URL and Multiple chats and history
• October 2025: 🔌 Model Context Protocol (MCP) support added for agentic capabilities with external tools
• September 2025: New Launcher application for MacOS and Linux, extended support to many backends for Mac and Nvidia L4T devices. Models: Added MLX-Audio, WAN 2.2. WebUI improvements and Python-based backends now ships portable python environments.
• August 2025: MLX, MLX-VLM, Diffusers and llama.cpp are now supported on Mac M1/M2/M3+ chips ( with development suffix in the gallery ): https://github.com/mudler/LocalAI/pull/6049 https://github.com/mudler/LocalAI/pull/6119 https://github.com/mudler/LocalAI/pull/6121 https://github.com/mudler/LocalAI/pull/6060
• July/August 2025: 🔍 Object Detection added to the API featuring rf-detr
• July 2025: All backends migrated outside of the main binary. LocalAI is now more lightweight, small, and automatically downloads the required backend to run the model. Read the release notes
• June 2025: Backend management has been added. Attention: extras images are going to be deprecated from the next release! Read the backend management PR.
• May 2025: Audio input and Reranking in llama.cpp backend, Realtime API, Support to Gemma, SmollVLM, and more multimodal models (available in the gallery).
• May 2025: Important: image name changes See release
• Apr 2025: Rebrand, WebUI enhancements
• Apr 2025: LocalAGI and LocalRecall join the LocalAI family stack.
• Apr 2025: WebUI overhaul, AIO images updates
• Feb 2025: Backend cleanup, Breaking changes, new backends (kokoro, OutelTTS, faster-whisper), Nvidia L4T images
• Jan 2025: LocalAI model release: https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.3, SANA support in diffusers: https://github.com/mudler/LocalAI/pull/4603
• Dec 2024: stablediffusion.cpp backend (ggml) added ( https://github.com/mudler/LocalAI/pull/4289 )
• Nov 2024: Bark.cpp backend added ( https://github.com/mudler/LocalAI/pull/4287 )
• Nov 2024: Voice activity detection models (VAD) added to the API: https://github.com/mudler/LocalAI/pull/4204
• Oct 2024: examples moved to LocalAI-examples
• Aug 2024: 🆕 FLUX-1, P2P Explorer
• July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723. P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
• May 2024: 🔥🔥 Decentralized P2P llama.cpp: https://github.com/mudler/LocalAI/pull/2343 (peer2peer llama.cpp!) 👉 Docs https://localai.io/features/distribute/
• May 2024: 🔥🔥 Distributed inferencing: https://github.com/mudler/LocalAI/pull/2324
• April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121

🚀 Features

• 🧩 Backend Gallery: Install/remove backends on the fly, powered by OCI images — fully customizable and API-driven.
• 📖 Text generation with GPTs (llama.cpp, transformers, vllm ... :book: and more)
• 🗣 Text to Audio
• 🔈 Audio to Text
• 🎨 Image generation
• 🔥 OpenAI-alike tools API
• ⚡ Realtime API (Speech-to-speech)
• 🧠 Embeddings generation for vector databases
• ✍️ Constrained grammars
• 🖼️ Download Models directly from Huggingface
• 🥽 Vision API
• 🔍 Object Detection
• 📈 Reranker API
• 🆕🖧 P2P Inferencing
• 🆕🔌 Model Context Protocol (MCP) - Agentic capabilities with external tools and LocalAGI's Agentic capabilities
• 🔊 Voice activity detection (Silero-VAD support)
• 🌍 Integrated WebUI!

🧩 Supported Backends & Acceleration

LocalAI supports a comprehensive range of AI backends with multiple acceleration options:

Text Generation & Language Models

Audio & Speech Processing

Image & Video Generation

Specialized AI Tasks

Hardware Acceleration Matrix

🔗 Community and integrations

Build and deploy custom containers:

• https://github.com/sozercan/aikit

• https://github.com/Jirubizu/localai-admin
• https://github.com/go-skynet/LocalAI-frontend
• QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot

• https://github.com/mudler/cogito

• https://github.com/mudler/MCPs

• https://github.com/mudler/Keygeist - Keygeist is an AI-powered keyboard operator that listens for key combinations and responds with AI-generated text typed directly into your Linux box.

• https://github.com/go-skynet/model-gallery

• https://github.com/richiejp/VoxInput

• Helm chart https://github.com/go-skynet/helm-charts
• VSCode extension https://github.com/badgooooor/localai-vscode-plugin
• Langchain: https://python.langchain.com/docs/integrations/providers/localai/
• Terminal utility https://github.com/djcopley/ShellOracle
• Local Smart assistant https://github.com/mudler/LocalAGI
• Home Assistant https://github.com/drndos/hass-openai-custom-conversation / https://github.com/valentinfrlch/ha-llmvision / https://github.com/loryanstrant/HA-LocalAI-Monitor
• Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
• Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
• Shell-Pilot(Interact with LLM using LocalAI models via pure shell scripts on your Linux or MacOS system) https://github.com/reid41/shell-pilot
• Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
• Another Telegram Bot https://github.com/JackBekket/Hellper
• Auto-documentation https://github.com/JackBekket/Reflexia
• Github bot which answer on issues, with code and documentation as context https://github.com/JackBekket/GitHelper
• Github Actions: https://github.com/marketplace/actions/start-localai
• Examples: https://github.com/mudler/LocalAI/tree/master/examples/

🔗 Resources

• LLM finetuning guide
• How to build locally
• How to install in Kubernetes
• Projects integrating LocalAI
• How tos section (curated by our community)

:book: 🎥 Media, Blogs, Social

• 🆕 LocalAI Autonomous Dev Team Blog Post

• Run Visual studio code with LocalAI (SUSE)
• 🆕 Run LocalAI on Jetson Nano Devkit
• Run LocalAI on AWS EKS with Pulumi
• Run LocalAI on AWS
• Create a slackbot for teams and OSS projects that answer to documentation
• LocalAI meets k8sgpt
• Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All
• Tutorial to use k8sgpt with LocalAI

🤖 Autonomous Development Team

LocalAI is now helped being maintained (for small tasks!) by a full team of autonomous AI agents led by an AI Scrum Master! This experiment demonstrates how open source projects can leverage AI agents for sustainable, long-term maintenance.

• 📊 Live Reports: Automatically generated reports
• 📋 Project Board: Agent task tracking
• 📝 Blog Post: Learn about the autonomous dev team experiment

Citation

If you utilize this repository, data in a downstream project, please consider citing it with:

@misc{localai,
  author = {Ettore Di Giacinto},
  title = {LocalAI: The free, Open source OpenAI alternative},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/go-skynet/LocalAI}},

❤️ Sponsors

Do you find LocalAI useful?

Support the project by becoming a backer or sponsor. Your logo will show up here with a link to your website.

A huge thank you to our generous sponsors who support this project covering CI expenses, and our Sponsor list:

Individual sponsors

A special thanks to individual sponsors that contributed to the project, a full list is in Github and buymeacoffee, a special shout out goes to drikster80 for being generous. Thank you everyone!

🌟 Star history

📖 License

LocalAI is a community-driven project created by Ettore Di Giacinto.

MIT - Author Ettore Di Giacinto

🙇 Acknowledgements

LocalAI couldn't have been built without the help of great software already available from the community. Thank you!

• llama.cpp
• https://github.com/tatsu-lab/stanford_alpaca
• https://github.com/cornelk/llama-go for the initial ideas
• https://github.com/antimatter15/alpaca.cpp
• https://github.com/EdVince/Stable-Diffusion-NCNN
• https://github.com/ggerganov/whisper.cpp
• https://github.com/rhasspy/piper

🤗 Contributors

This is a community project, a special thanks to our contributors! 🤗