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LocalAI

LocalAI is a free, open-source, self-hosted AI engine that provides a drop-in, OpenAI-compatible API for running local models.

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LocalAI is a free, open-source, self-hosted AI engine that provides a drop-in, OpenAI-compatible API for running local models. It runs text, audio (including voice cloning), image and video models — including GGUF, transformers and diffusers architectures — on consumer-grade hardware, with no GPU required, and pulls each model backend only when needed. It is aimed at homelab users who want OpenAI-style inference on their own hardware, without depending on cloud services.

Platform availability

Available on 5 of 6 install platforms

Also on GitHub

Health score

51/100 Fair

Maintained
No data
Popular
No data
Easy to install
755 install platforms, install notes, Docker image
Light to run
2016 GB minimum RAM, runs on ARM

Based on 2 of 4 factors.

How is this calculated?

A 0-100 score computed nightly from four factors: maintained (40%: recent commits and steady activity), popular (25%: GitHub stars, log scale), easy to install (20%: platforms, install notes, setup guides, Docker image) and light to run (15%: minimum RAM, ARM support). Factors without data are left out and the rest are rescaled.

Availability: platform listings confirmed today, links checked 11 days ago

GitHub stars
49,451
Open issues
188
Last commit
2026-10-09
Latest release
v4.11.0
License
MIT
Activity
steady

Checked today - source: GitHub (mudler/LocalAI)

Resources & Compatibility

Minimum requirements: 16 GB RAM, 4 CPU core(s). ARM (e.g. Raspberry Pi) is supported.

Checked 10 days ago - source: Docker Hub image tags and published docs

First-install notes

  • Map port 8080 when starting LocalAI Start LocalAI with port 8080 mapped to your machine, like the Docker example's `-p 8080:8080`, so your browser or apps can connect. Without the port mapping, LocalAI may be running but you cannot reach it. source
  • Install a model and its backend first Before using LocalAI, install the backend the model needs (for example llama-cpp) and install at least one model with the provided command. If a backend or model is missing, requests will fail because LocalAI has nothing to load. source
  • Test the API after setup After starting LocalAI and installing a model, send a test chat completion request to the /v1/chat/completions endpoint. This helps you confirm the service, model, and network path are working before connecting other apps. source

Fetched 10 days ago - each note links to its source

Alternatives (12)

  • Alpaca - Ollama Client - Alpaca is an Ollama client where you can manage and chat with multiple models, Alpaca provides an easy and begginer friendly way of interac…
  • AnythingLLM - The all-in-one AI app for any LLM with full RAG and AI Agent capabilities.
  • ChatGPT - ChatGPT is a generative artificial intelligence chatbot developed by OpenAI and launched in 2022.
  • Cherry Studio - Cherry Studio is a desktop client that supports for multiple LLM providers, available on Windows, Mac, and Linux.
  • DeepSeek - DeepSeek is a state-of-the-art AI assistant designed to provide intelligent, conversational support across diverse tasks.
  • Ensu - Private offline on-device local LLM app by Ente, open source code, no accounts or tracking, and works cross-platform on mobile and desktop…
  • Euria - Privacy-first AI assistant with chat, writing, transcription, summarization, email, and document tools, hosted in Switzerland and compliant…
  • GPT4ALL - GPT4All runs open-source large language models (LLMs) privately on your own hardware, providing a local chat interface and server that need…
  • Google AI Edge Gallery - A gallery that showcases on-device ML/GenAI use cases and allows people to try and use models locally.
  • Google Gemini - Gemini gives you direct access to Google AI.
  • Jan.ai - Open-source offline AI chat software supporting local LLMs, cloud model connections, custom assistant creation, OpenAI-compatible API, and…
  • LM Studio - Run large language models offline with a built-in chat UI, OpenAI-compatible server, HuggingFace integration, local discovery, private mode…

Checked 7 days ago - source: AlternativeTo

Common questions

How do I make LocalAI reachable from my browser or apps?

Map port 8080 when starting LocalAI, such as Docker's -p 8080:8080, so your browser or apps can connect. If the port is not mapped, LocalAI may be running but you cannot reach it.

What must I install before a model can run?

Install the backend the model needs, for example llama-cpp, and install at least one model with the provided command. If a backend or model is missing, requests fail because LocalAI has nothing to load.

Where does LocalAI store model files?

Command line uses ./models, Docker uses /models inside the container typically mounted to ./models, and the launcher uses ~/.localai/models. You can customize the model storage location with the LOCALAI_MODELS_PATH environment variable.

How can I test LocalAI after setup?

After starting LocalAI and installing a model, send a test chat completion request to the /v1/chat/completions endpoint. This confirms the service, model, and network path are working before connecting other apps.

Can I point an existing OpenAI client at LocalAI?

Point an existing client at LocalAI as a drop-in replacement for most OpenAI API calls. It also speaks the Anthropic, Ollama, and ElevenLabs APIs, so most tools need only a URL change.

Answers sourced from localai.io, localai.io, localai.io, localai.io, localai.io

Community

Collected 4 days ago - public community threads