AnalysisOpinion / analysisHardware & Compute · Efficiency & Inference1 source · Oct 13, 2026

I clustered two old Android phones to run a 27B LLM locally. Bypassed RAM limits via C++ RPC split and Hadamard Ternary math (No overheating)

I saw a lot of posts here struggling to run 27B models on 8GB VRAM or complaining about phones turning into space heaters.

Proof1 community thread

Key points

  • I wrote a custom C++ engine (fork of llama.rn) to cluster two Android phones over a simple USB cable.
  • Model: Ternary-Bonsai-2-27B (compressed to 2.06 bpw / 6.52 GiB).
  • Cluster Mode (Xiaomi redme 100 pro max + ROG 7): Layers are split 4.36 GiB / 2.15 GiB over the USB cable via custom RPC.
  • Speed: ~2.8 tok/s (bottlenecked by the slower phone, but perfectly synced).

Sources (1)

Extractive summary: sentences quoted from the sources.

Before this

  1. Oct 13, 2026Hybrid Reasoning Agents
  2. Oct 13, 2026Fish Audio Drama 3 Technical Report
  3. Oct 12, 2026openbmb/MiniCPM-V-4.7-1B
  4. Oct 12, 2026openbmb/MiniCPM-V-4.7-35B-A3B
  5. Oct 12, 2026Deploy decision models with llama.cpp on Amazon SageMaker AI
  6. Oct 12, 2026unslothai/unsloth v0.1.906-beta: Browser Use + Qwen-Image-2.1-Turbo

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