LocalAI
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
- 49.9k estrellas
- 4.5k forks
- 220 issues abiertos
- Lenguaje: Go
- Licencia: MIT
- actualizado
Instalación
git clone https://github.com/mudler/LocalAI && cp LocalAI/*.md ~/.claude/agents/- Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
- Start a new Claude Code session to load the agents.
- Delegate work to them with the Task/Agent tool or by name.
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.
Resumen de Subagents
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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.
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

Created by Ettore Di Giacinto and maintained by the LocalAI team.
:book: Documentation | :speech_balloon: Discord | 💻 Quickstart | 🖼️ Models | ❓FAQ
Guided tour
https://github.com/user-attachments/assets/08cbb692-57da-48f7-963d-2e7b43883c18
Click to see more!
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
Quickstart
macOS
Note: The DMG is not signed by Apple. After installing, run:
sudo xattr -d com.apple.quarantine /Applications/LocalAI.app. See #6268 for details.
Containers (Docker, podman, ...)
Already ran LocalAI before? Use
docker start -i local-aito restart an existing container.
CPU only:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latestNVIDIA GPU:
# 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-13AMD GPU (ROCm):
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblasIntel GPU (oneAPI):
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intelVulkan GPU:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkanLoading models
# 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:latestTo work with a running LocalAI server from the terminal, start the built-in agent from another shell. It answers questions, reads your files and runs commands on your machine, asking you to approve anything that changes state. Inside a session, /models lists installed models and /model switches between them. See the Terminal agent docs.
# 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_mAutomatic Backend Detection: LocalAI automatically detects your GPU capabilities and downloads the appropriate backend. For advanced options, see GPU Acceleration.
For more details, see the Getting Started guide.
Latest News
October 2026: LocalAI 4.11.0 — Audio scenes with transcription, speaker labels, and sound detection. Also the Decisions API (
/v1/systemone), model failover chains, signed OCI galleries, and Kimodo text-to-animation. Release notesSeptember 2026: LocalAI 4.10.0 — A fleet operations dashboard, one credentials file for private model sources, and
local-ai benchmarkfor measuring model latency and throughput. Release notesAugust 2026: LocalAI 4.9.0 — Deny-by-default authentication, opt-in chat context compression, unified model and backend management, and MiniMax-H3 video generation with audio. Release notes
August 2026: LocalAI 4.8.0 — Introducing vllm.cpp (alpha development builds), image-to-3D generation with a built-in viewer, and
audio.cppfor speech, transcription, VAD, diarization, source separation and sound generation. Release notesJuly 2026: LocalAI 4.7.0 — Managed voice cloning profiles, local video and talking-avatar generation, and interleaved reasoning with tool calls. Release notes
July 2026: LocalAI 4.6.0 — AMD ROCm fixes, predictable realtime pipeline warmup, conversation forking, and more reliable distributed model loading. Release notes
June 2026: LocalAI 4.5.0 — Native depth estimation and sound-event detection, NER-based PII filtering, and speaker-aware realtime conversations with automatic history compaction. Release notes
Older news
June 2026: New native biometric backends from the LocalAI team: voice-detect.cpp for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and 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
insightfaceandspeaker-recognitionbackends (PR #10441).
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 49.9k estrellas en GitHub y su última actualización registrada es del 2026-10-23.
¿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 100/100 (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 del 2026-10-23, con 220 issues abiertos.
¿Hay alternativas a LocalAI?
Sí. En ClaudeWave puedes explorar subagents similares en /categories/agents, ordenados por popularidad o actividad reciente.
¿Mantienes este repo? Muestra su Trust Score en tu README
La insignia muestra el Trust Score y el veredicto actuales de este repositorio y enlaza a esta página. Sigue los datos del catálogo: nadie puede comprar ni editar la puntuación que enseña.
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