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LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.

Subagents47.9k estrellas4.3k forksGoMITActualizado today
Nota editorial

LocalAI is a self-hosted, open-source AI inference engine written in Go that exposes OpenAI, Anthropic, and ElevenLabs compatible REST APIs, letting developers run LLMs, vision models, speech recognition, text-to-speech, image generation, and video models entirely on local hardware without mandatory GPU. Each modality delegates to a specialist backend such as llama.cpp, vLLM, MLX, whisper.cpp, stable-diffusion, or kokoro, and those backends are pulled as separate container images only when a matching model is loaded, so unused capabilities consume no disk space. Models can be pulled from the built-in gallery, Hugging Face, Ollama's OCI registry, or standard Docker registries via a single CLI command. The project connects to the Claude ecosystem through its Anthropic API compatibility layer and built-in MCP support, meaning Claude Code or any MCP-aware client can route requests through a LocalAI instance instead of Anthropic's cloud. Built-in autonomous agents support tool use and RAG. Multi-user deployments get API key authentication, per-user quotas, and role-based access controls, making the project relevant to privacy-conscious teams, on-premises enterprise deployments, and developers building Claude-compatible applications without sending data off-site.

ClaudeWave Trust Score
93/100
Verified

Self-hosted OpenAI-compatible inference engine that runs LLMs, vision, voice and image models locally without a GPU.

Passed
  • Open-source license (MIT)
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
  • Mature repo (>1y old)
OK to use
Last scanned: 6/11/2026
Install as a Claude Code subagent
Method: Clone
Terminal
git clone https://github.com/mudler/LocalAI && cp LocalAI/*.md ~/.claude/agents/
1. Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
2. Start a new Claude Code session to load the agents.
3. Delegate work to them with the Task/Agent tool or by name.
Casos de uso

Resumen de Subagents

<h1 align="center">
  <br>
  <img width="300" src="./core/http/static/logo.png"> <br>
<br>
</h1>

<p align="center">
<a href="https://github.com/go-skynet/LocalAI/stargazers" target="blank">
<img src="https://img.shields.io/github/stars/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI stars"/>
</a>
<a href='https://github.com/go-skynet/LocalAI/releases'>
<img src='https://img.shields.io/github/release/go-skynet/LocalAI?&label=Latest&style=for-the-badge'>
</a>
<a href="LICENSE" target="blank">
<img src="https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge" alt="LocalAI License"/>
</a>
</p>

<p align="center">
<a href="https://twitter.com/LocalAI_API" target="blank">
<img src="https://img.shields.io/badge/X-%23000000.svg?style=for-the-badge&logo=X&logoColor=white&label=LocalAI_API" alt="Follow LocalAI_API"/>
</a>
<a href="https://discord.gg/uJAeKSAGDy" target="blank">
<img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Discord&style=for-the-badge&query=approximate_member_count&url=https%3A%2F%2Fdiscordapp.com%2Fapi%2Finvites%2FuJAeKSAGDy%3Fwith_counts%3Dtrue&logo=discord" alt="Join LocalAI Discord Community"/>
</a>
</p>

<p align="center">
<a href="https://trendshift.io/repositories/5539" target="_blank"><img src="https://trendshift.io/api/badge/repositories/5539" alt="mudler%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>

<!-- Keep these links, translations synced daily. -->
<p align="center">
<a href="https://zdoc.app/de/mudler/LocalAI">Deutsch</a> |
<a href="https://zdoc.app/es/mudler/LocalAI">Español</a> |
<a href="https://zdoc.app/fr/mudler/LocalAI">français</a> |
<a href="https://zdoc.app/ja/mudler/LocalAI">日本語</a> |
<a href="https://zdoc.app/ko/mudler/LocalAI">한국어</a> |
<a href="https://zdoc.app/pt/mudler/LocalAI">Português</a> |
<a href="https://zdoc.app/ru/mudler/LocalAI">Русский</a> |
<a href="https://zdoc.app/zh/mudler/LocalAI">中文</a>
</p>

**LocalAI** is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.

**A small core, not a bundle.** Each backend wraps a best-in-class engine (llama.cpp, vLLM, whisper.cpp, stable-diffusion, MLX...) in its own image, pulled only when a model needs it. You install nothing you don't use.

- **Composable by design**: backends are separate and pulled on demand, so you install only what your model needs
- **Open and extensible**: load any model, or build your own backend in any language against an open interface
- **Drop-in API compatibility**: OpenAI, Anthropic, and ElevenLabs APIs across every backend
- **Any model, any modality**: LLMs, vision, voice, image, and video behind one API
- **Any hardware**: NVIDIA, AMD, Intel, Apple Silicon, Vulkan, or CPU-only
- **Multi-user ready**: API key auth, user quotas, role-based access
- **Built-in AI agents**: autonomous agents with tool use, RAG, MCP, and skills
- **Privacy-first**: your data never leaves your infrastructure

![A small LocalAI core with backends (llama.cpp, vLLM, MLX, whisper.cpp, stable-diffusion, kokoro, parakeet.cpp...) plugged in as separate on-demand images](docs/static/images/diagrams/composable-core.png)

Created by [Ettore Di Giacinto](https://github.com/mudler) and maintained by the [LocalAI team](#team).

> [:book: Documentation](https://localai.io/) | [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) | [💻 Quickstart](https://localai.io/basics/getting_started/) | [🖼️ Models](https://models.localai.io/) | [❓FAQ](https://localai.io/faq/)

## Guided tour

https://github.com/user-attachments/assets/08cbb692-57da-48f7-963d-2e7b43883c18

<details>

<summary>
Click to see more!
</summary>

#### User and auth

https://github.com/user-attachments/assets/228fa9ad-81a3-4d43-bfb9-31557e14a36c

#### Agents

https://github.com/user-attachments/assets/6270b331-e21d-4087-a540-6290006b381a

#### Usage metrics per user

https://github.com/user-attachments/assets/cbb03379-23b4-4e3d-bd26-d152f057007f

#### Fine-tuning and Quantization

https://github.com/user-attachments/assets/5ba4ace9-d3df-4795-b7d4-b0b404ea71ee

#### WebRTC

https://github.com/user-attachments/assets/ed88e34c-fed3-4b83-8a67-4716a9feeb7b

</details>

## Quickstart

### macOS

<a href="https://github.com/mudler/LocalAI/releases/latest/download/LocalAI.dmg">
  <img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
</a>

> **Note:** The DMG is not signed by Apple. After installing, run: `sudo xattr -d com.apple.quarantine /Applications/LocalAI.app`. See [#6268](https://github.com/mudler/LocalAI/issues/6268) for details.

### Containers (Docker, podman, ...)

> Already ran LocalAI before? Use `docker start -i local-ai` to restart an existing container.

#### CPU only:

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

#### NVIDIA GPU:

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

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

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

# NVIDIA Jetson ARM64 (CUDA 13, for DGX Spark)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13
```

#### AMD GPU (ROCm):

```bash
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 (oneAPI):

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

#### Vulkan GPU:

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

### Loading models

```bash
# From the model gallery (see available models with `local-ai models list` or at https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# From Huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# From the Ollama OCI registry
local-ai run ollama://gemma:2b
# From a YAML config
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# From a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest
```

To test a running LocalAI server from the terminal, open an interactive chat session from another shell. Inside the prompt, `/models` lists installed models and `/model <name>` switches between them.

```bash
# Terminal 1
local-ai run llama-3.2-1b-instruct:q4_k_m

# Terminal 2
local-ai chat --model llama-3.2-1b-instruct:q4_k_m
```

> **Automatic Backend Detection**: LocalAI automatically detects your GPU capabilities and downloads the appropriate backend. For advanced options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/).

For more details, see the [Getting Started guide](https://localai.io/basics/getting_started/).

## Latest News

- **June 2026**: New native biometric backends from the LocalAI team: [voice-detect.cpp](https://github.com/localai-org/voice-detect.cpp) for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and [face-detect.cpp](https://github.com/mudler/face-detect.cpp) for face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace). Both are from-scratch C++/ggml engines with no Python or onnxruntime at inference, self-contained GGUF weights, bit-exact parity with the reference, and GPU cuDNN parity, replacing the heavier Python `insightface` and `speaker-recognition` backends ([PR #10441](https://github.com/mudler/LocalAI/pull/10441)).
- **June 2026**: New [realtime voice assistant demo](https://github.com/localai-org/localai-realtime-demo) (a tiny Go client for the Realtime API with a full talk-back voice loop and tool calling), plus [streaming of the realtime LLM / TTS / transcription pipeline stages](https://github.com/mudler/LocalAI/pull/10176) and [configurable WebRTC ICE candidates](https://github.com/mudler/LocalAI/pull/10231).
- **June 2026**: Big speech push: the [parakeet.cpp](https://github.com/mudler/parakeet.cpp) ASR engine gains [NeMo-faithful segment timestamps](https://github.com/mudler/LocalAI/pull/10207), a [multilingual streaming Nemotron-3.5 model](https://github.com/mudler/LocalAI/pull/10199), [dynamic batching for concurrent transcription](https://github.com/mudler/LocalAI/pull/10112) and [CUDA graphs](https://github.com/mudler/LocalAI/pull/10273); the new [CrispASR backend](https://github.com/mudler/LocalAI/pull/10099) adds multi-architecture ASR + TTS, and [60 Piper TTS voices across 42 languages](https://github.com/mudler/LocalAI/pull/10296) land in the gallery (plus [per-request TTS instructions and params](https://github.com/mudler/LocalAI/pull/10172)).
- **June 2026**: New backends and models: [locate-anything.cpp](https://github.com/mudler/LocalAI/pull/10264) for open-vocabulary object detection via ggml, [Ideogram4 image generation](https://github.com/mudler/LocalAI/pull/10201) in stablediffusion-ggml, [llama.cpp video input](https://github.com/mudler/LocalAI/pull/10216), and the [Gemma 4 QAT family with MTP speculative-decoding pairs](https://github.com/mudler/LocalAI/pull/10215). Plus an [interactive CLI chat mode](https://github.com/mudler/LocalAI/pull/10226) and [RAG source citations in agent responses](https://github.com/mudler/LocalAI/pull/10228).
- **June 2026**: Distributed mode hardening: [prefix-cache-aware routing](https://github.com/mudler/LocalAI/pull/10071), a [production-ready request router with auto-sized embedding/rerank batches](https://github.com/mudler/LocalAI/pull/10104), [ds4 layer-split distributed inference](https://github.com/mudler/LocalAI/pull/10098), [NATS JWT auth + TLS/mTLS](https://github.com/mudler/LocalAI/pull/1
agentsaiapiaudio-generationdecentralizeddistributedimage-generationlibp2pllamallmmambamcpmusicgenobject-detectionrerankstable-diffusiontext-generationtts

Lo que la gente pregunta sobre LocalAI

¿Qué es mudler/LocalAI?

+

mudler/LocalAI es subagents para el ecosistema de Claude AI. LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required. Tiene 47.9k estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala LocalAI?

+

Puedes instalar LocalAI clonando el repositorio (https://github.com/mudler/LocalAI) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar mudler/LocalAI?

+

Nuestro agente de seguridad ha analizado mudler/LocalAI y le ha asignado un Trust Score de 93/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene mudler/LocalAI?

+

mudler/LocalAI es mantenido por mudler. La última actividad registrada en GitHub es de today, con 207 issues abiertos.

¿Hay alternativas a LocalAI?

+

Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.

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