# Dev proves LLMs will run on anything – even a $10 microcontroller

- URL: https://talkfuse.com/story/dev-proves-llms-will-run-on-anything-even-a-10-microcontroller/
- Published: 2026-08-04T21:20:00+00:00
- Updated: 2026-08-04T21:33:13+00:00
- Original publisher: The Register
- Original article: https://www.theregister.com/edge-and-iot/2026/08/04/dev-proves-llms-will-run-on-anything-even-a-10-microcontroller/5283088
- Topics: AI, Geopolitics, Politics, Technology

## Key points

- Developer ran a small LLM on a sub-$10 ESP32 microcontroller
- Used quantisation and flash offloading to shrink memory needs drastically
- Achieved nearly 10 tokens per second, faster than human reading speed

## Summary

A developer known as SlvDev has demonstrated that even a large language model can run on an ESP32-S3 microcontroller costing less than $10, a device normally used for basic sensors and IoT tasks rather than generative AI. The feat, documented on GitHub and showcased on the Better Stack YouTube channel, shows how aggressive memory-saving techniques can squeeze AI workloads onto hardware far too small and cheap to handle them by conventional means.

To achieve this, SlvDev used TinyStories, a 28.9-million-parameter model from Microsoft Research, roughly 10,000 times smaller than modern frontier models. Quantisation cut the model's memory footprint from 60MB to 14.9MB, and a technique borrowed from Google's Gemma models, called per-layer embedding, offloaded around 12MB of weights to flash storage, leaving only about 2MB needed in active memory. The result was a working chatbot-style model running at 9.88 tokens per second on the ESP32-S3's 520KB of SRAM and 8MB of PSRAM, faster than the average person can read.

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Summarised by TalkFuse (https://talkfuse.com/). Quote the original publisher for the reporting and link this page for the summary and discussion.