Side-by-side
| Axis | Raspberry Pi 5 | Intel NUC 13 |
|---|---|---|
| Setup time | Raspberry Pi OS Bookworm flash, Docker, Hermes Agent — 60-90 minutes from box to running agent. Bring your own SD card or NVMe HAT. | Ubuntu 24.04 LTS install, Docker, Hermes Agent — 45 minutes from box to running agent. Internal NVMe ships with the unit. |
| Security model | ARM Cortex-A76 has Pointer Authentication; useful but not a panacea. No hardware TPM by default. | Intel TXT and TPM 2.0 supported. Intel Boot Guard for verified boot. Hardware-rooted attestation possible. |
| Model support | Comfortable up to 3B Q4 (~7 tok/s on qwen2.5-coder-3B). 7B starts hurting at 4 tok/s. 14B+ unrealistic. | Comfortable up to 7B Q4 (~11 tok/s on qwen2.5-coder-7B). 14B Q4 runs at 6 tok/s — slow but usable. 32B is unrealistic without GPU. |
| Cost | €138 hardware. €4.30/month total cost of ownership including electricity. | €620 hardware. €25/month total cost of ownership including electricity. |
| Ecosystem | Raspberry Pi has the largest single-board-computer community on Earth. Every problem has been solved by someone, somewhere. | Standard x86. Anything that runs on a Linux laptop runs on a NUC. |
| Best for | Edge classification, agent orchestration, small-model workloads. Or anyone learning self-hosted AI cheaply. | Mid-volume self-hosted AI on 7B models, or workloads where you'd otherwise want a laptop minus the screen. |
Verdict
Pi 5 if your workload fits inside 3B. NUC 13 if you need 7B with margin. Both lose to Mac Mini M4 on tokens-per-watt; both win against the GPU box on idle power and price. Choose by model size, not headline brand.
Notes
- Pi 5 needs a fan — passive cooling alone throttles in five minutes of LLM work.
- NUC 13's Iris Xe iGPU helps a little on inference; Vulkan or SYCL backend in llama.cpp can pull 20% more tokens/s.
- If you're going to add NVMe, a Mac Mini M4 24 GB is often a better dollar-for-dollar buy than a NUC + storage.
Going deeper
For the full landscape report including hosting economics, security posture and regulatory context, see the 2026 landscape report. For the OpenClaw-specific history, see the complete OpenClaw timeline.
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