Best NAS for Self-Hosted AI Services (2026)
Best NAS devices for running AI models and self-hosted AI services. Synology, QNAP with GPU support, and DIY NAS builds for local LLM inference.
Last updated: February 7, 2026
🎯 Why This Matters
A NAS (Network Attached Storage) can double as an AI server, running models 24/7 for your whole household or team. Modern NAS devices from QNAP and Synology support Docker containers and some even have PCIe slots for GPUs. A NAS-based AI setup means always-available inference, centralized model storage, and integration with your existing home server setup.
🏆 Our Recommendations
Tested and ranked by real-world AI performance
Synology DS923+ (32GB RAM upgrade)
✅ Pros
- Great NAS that also does AI
- Docker support via Container Manager
- 32GB RAM fits 7B models
- Reliable Synology ecosystem
- Low power consumption
❌ Cons
- Slow CPU for AI inference
- No GPU slot
- Only 7B models realistically
- Embedded CPU limitations
QNAP TS-AI642 (NPU-equipped)
✅ Pros
- Built-in NPU for AI acceleration
- PCIe slot for future GPU
- Expandable to 64GB RAM
- QNAP AI ecosystem
- 6 drive bays
❌ Cons
- $899 before drives
- NPU support for LLMs still maturing
- QNAP software less polished than Synology
- Need to buy RAM upgrade separately
DIY NAS Build (TrueNAS + GPU)
✅ Pros
- GPU-accelerated AI inference
- Full NAS functionality
- Highly customizable
- Can run any AI framework
- TrueNAS is enterprise-grade
❌ Cons
- Requires building and configuring
- Higher power consumption
- More noise than commercial NAS
- No vendor support
💡 Prices may vary. Links may earn us a commission at no extra cost to you. We only recommend products we'd actually use.
🤖 Compatible Models
Models you can run with this hardware
❓ Frequently Asked Questions
Can a NAS really run AI models?
Yes, but with limitations. Commercial NAS devices run 7B models at 4-12 tok/s via CPU inference in Docker. For faster inference, build a DIY NAS with a GPU. The advantage is 24/7 availability — your AI is always ready, like having a personal ChatGPT server.
Synology vs QNAP for AI?
QNAP is ahead for AI-specific features — some models have NPUs and PCIe slots for GPUs. Synology has better software polish and ecosystem but limited AI hardware options. For pure AI focus, QNAP or DIY. For NAS-first with light AI, Synology.
Should I use my NAS for AI or get a separate machine?
If you already have a NAS, try running Ollama in Docker first. If it's too slow, get a dedicated mini PC or desktop with a GPU. Running AI on your NAS is convenient but compute-limited unless you go DIY with a GPU.
Ready to build your AI setup?
Pick your hardware, install Ollama, and start running models in minutes.