ESP32S3 cluster running 1.58-bit (BitNet) Language model

What changed

A distributed pipeline inference engine on multiple ESP32S3 running 1.58-bit (BitNet) Language model. This project runs a sliced 0.5B LLM across a cluster of 7 ESP32s3. One act as master and others are node.

Why it matters

A concrete addition to Practical AI: Tools, Models & Frameworks: it changes what's available to builders today rather than being general commentary.

How it compares

Related prior coverage to compare against:

• Running a 28.9M parameter LLM on an $8 microcontroller
• AirLLM 70B inference with single 4GB GPU
• The efficient frontier of LLM inference

• Running a 28.9M parameter LLM on an $8 microcontroller similarity 0.42
• AirLLM 70B inference with single 4GB GPU similarity 0.37
• The efficient frontier of LLM inference similarity 0.36