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OpenClaw 88,412 stars·CVE-2026-25898 disclosed (HIGH, Hermes)·Hermes Agent v2026.4.7 published·Hermes Agent +182 stars (last hour)·OpenClaw v2026.4.6 — credential vault hardening·CVE-2026-26133 patched (NanoClaw)·Pi 5 16GB rumoured for Q3 — recheck guidance·Nanobot +47 stars (last hour)·ZeroClaw v0.4.2 — Apple container fixes·Mac Mini M4 wins quarterly hardware survey·OpenClaw 88,412 stars·CVE-2026-25898 disclosed (HIGH, Hermes)·Hermes Agent v2026.4.7 published·Hermes Agent +182 stars (last hour)·OpenClaw v2026.4.6 — credential vault hardening·CVE-2026-26133 patched (NanoClaw)·Pi 5 16GB rumoured for Q3 — recheck guidance·Nanobot +47 stars (last hour)·ZeroClaw v0.4.2 — Apple container fixes·Mac Mini M4 wins quarterly hardware survey·
PocketClawvol. 1 · 2026
Worth it★★★★

Nanobot on Raspberry Pi 5

Verdict

Nanobot on a Pi 5 (8 GB) is the most quietly capable setup at this price tier. The Python codebase fits trivially in the available RAM, and you can pair it with Ollama running Phi-3 mini for an entirely local, entirely auditable, entirely cheap agent stack. No sandbox by design, single-user by design — match those to your threat model first.

Setup notes

Pi OS Bookworm, Python 3.11, virtualenv. Install Nanobot from PyPI. Install Ollama for ARM (the Pi 5 builds work). Pull Phi-3 mini 3.8B Q4. Point Nanobot at Ollama.

Performance

Nanobot itself: ~80 MB RAM, ~3% CPU idle. Phi-3 mini Q4: 6 tok/s. Total stack: comfortably under 4 GB RAM, leaves headroom for tools and OS.

What breaks

  • Multi-user
  • Anything requiring 7B+ local model capability

Want to know more

See the full Nanobot review and the Raspberry Pi 5 buyer's notes.

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