⬢github C++ · 106 ★ +49 since we first saw it · pushed 2 d ago · MIT
Low-Zi-Hong/ESP32s3-LLM-Cluster
7-node ESP32-S3 cluster running a 0.4B LLM via 1.58-bit (BitNet) ternary quantization over SPI daisy-chain
A hobbyist hardware project that runs a ~0.5B-parameter LLM split across a cluster of seven ESP32-S3 microcontroller boards. One master board handles the tokenizer and embeddings; six compute nodes each execute several transformer layers using 1.58-bit BitNet ternary quantization, passing hidden states along a high-speed SPI daisy-chain to generate text.
Why now: It was featured on Hacker News, likely because running a transformer LLM on cheap microcontrollers via BitNet quantization is a surprising and impressive demo.
Who it is for: Embedded and hardware hobbyists curious about extreme model quantization and running neural networks on microcontrollers.
Stars over our 29 snapshots: 57 to 106, since 7 h ago.
Where people talked about it
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