AI Homelab with OpenClaw
Turn any spare hardware — an old Mac Mini, a NUC, a used server — into a private AI workstation running local LLMs 24/7. No cloud. No subscriptions. Your AI, your hardware, your data.
OpenClaw orchestrates Ollama, tool access, memory, and messaging channels from one persistent hub. Message it on Telegram while it's running on your network closet. It's always on, always context-aware.
Why cloud AI is holding you back
Cloud AI assistants are convenient — until you actually need them to do real work. They disconnect after every answer. They have no memory of your life. They send your emails, calendar, and data to servers you don't control. And at scale, API costs add up fast: $3–$15 per hour for frontier models.
Meanwhile, your old Mac Mini or spare server is sitting idle. The local AI ecosystem has matured — Ollama runs hundreds of models with one command, and models like Llama 3.1, Mistral, and Gemma 4 are genuinely capable. The hardware you already have is smarter than the subscription you're paying for.
Your AI homelab, powered by OpenClaw
OpenClaw turns your homelab into an AI assistant that never sleeps, never forgets, and never sends your data to the cloud.
One command installs OpenClaw. Connect it to Ollama (for local models), or any API provider (OpenAI, Anthropic, Google). OpenClaw handles the routing.
Telegram, Discord, WhatsApp, iMessage — connect the channels you actually use. OpenClaw becomes reachable from anywhere, on any device, via chat.
Attach email, calendar, code execution, web search, or any skill. OpenClaw uses your models (local or API) to decide when to call what. Local models work fine for most automations.
OpenClaw persists. Unlike cloud AI that disconnects after every answer, your homelab AI is always on, always context-aware, always ready. Wake up and it's already run your morning reports.
What hardware works for an AI homelab?
OpenClaw runs on anything. Local LLM inference scales with your budget. Here are the most common homelab setups:
Silent, energy-efficient, and surprisingly powerful. An M2 Mac Mini handles 7B–13B models smoothly. Many users run full homelabs on a $600–$800 unit.
Small, cheap, expandable. A used NUC12 can run 7B models at ~20 tokens/sec. Good entry point if you already have one sitting around.
Dell Precision, HP Z-series, or a dedicated home server. Max out RAM and GPU for 70B+ model performance. More power, more noise, more electricity.
Don't throw it out. An old gaming PC with a GPU upgrade (3090, 4090, 5090) becomes a serious AI inference machine. OpenClaw runs fine on modest hardware too.
Three popular AI homelab setups
Start building your AI homelab today
OpenClaw's getting started guide walks you through installing on Mac Mini, NUC, VPS, or any Linux machine. Most people are up and running in under 30 minutes.
Get Started Free →AI Homelab FAQ
What exactly is an AI homelab?
An AI homelab is a private server or computer running AI models locally — no cloud, no API calls to external servers. You own the hardware, own the models, own the data. OpenClaw turns that hardware into a full AI assistant with tool access, memory, and messaging integrations.
Why run AI in a homelab instead of using cloud APIs?
Privacy, cost, and persistence. Cloud AI sends your prompts and data to third-party servers. A homelab keeps everything local. At scale, local inference costs $0.40–$2/hr of GPU time versus $3–$15/hr for API calls. And unlike cloud AI that starts fresh every conversation, your homelab AI remembers everything across sessions — 24/7.
What hardware do I need for an AI homelab with OpenClaw?
OpenClaw itself is lightweight — it runs fine on a Raspberry Pi for light tasks. For local LLM inference, you'll want at least 16GB RAM (32GB recommended) and ideally a GPU with 8GB+ VRAM. A Mac Mini M1/M2, Intel NUC with a GPU, or an old gaming PC with a 3090/4090 are the most common choices. See the hardware table above for specifics.
What local models work well with OpenClaw?
Ollama supports hundreds of models. For homelab use, Llama 3.1 8B, Mistral 7B, Gemma 4 9B, and Qwen 2.5 14B offer the best balance of capability and speed on consumer hardware. If you have a 3090/4090, you can run Llama 3.1 70B at usable speeds. OpenClaw works with any Ollama model — or you can mix local + API models depending on the task.
Does OpenClaw have to use local models?
No. OpenClaw connects to local models via Ollama, but also supports any OpenAI-compatible API — Anthropic, OpenAI, Google Gemini, Groq, and more. Many users run local models for simple tasks (reminders, summaries, automation) and route complex reasoning to cloud APIs. OpenClaw orchestrates both seamlessly.
Is a homelab AI secure?
Significantly more than cloud AI. Your data never leaves your network. OpenClaw supports TLS, authentication gates, Docker sandboxing, and network isolation. There's no server sending your conversations to a third party. The main attack surface is your home network — which you control.
How is this different from just running Ollama alone?
Ollama is an inference engine — it runs models. OpenClaw is an AI assistant framework — it connects models to the real world. Without OpenClaw, you'd manually prompt Ollama, copy-paste results, and manually trigger actions. With OpenClaw, you message it on Telegram and it sends emails, checks your calendar, runs code, searches the web, and remembers everything between conversations.
Can I run multiple AI agents on my homelab?
Yes. OpenClaw supports multi-agent setups where specialized agents handle different domains — a researcher, a writer, a code reviewer — all running on your homelab simultaneously. You can run them as separate OpenClaw instances or use the built-in multi-agent orchestration.
Your AI homelab awaits
OpenClaw is free and open source. Install it on your hardware tonight and wake up to an AI that already ran your morning reports.