Hobbyist trains a diffusion model on a 264KB-RAM microcontroller, ~70s per image
PandaBean18 · reddit · 2026-08-18
A Reddit user trained a diffusion model that generates 32×32 images on a Shrike Lite microcontroller with only 264KB of SRAM.
Key details:
- The board's onboard FPGA was used to build two parallel INT8 MAC engines with 16-bit accumulation, but the system hit a memory wall from heavy I/O — the parallel setup was slower (220s/image) than MCU-only (70s/image).
- Heavy quantization and memory limits made many outputs noisy and weird, though some came out cool.
- Full case study linked in the post.
More from Infra
- 5 dual-L40 hosts running vLLM leave ~5GB idle VRAM per GPU — how to use it? — gulensah · 2026-08-18
- AltRouter proposes open-source resource pooling for cost-effective local model hosting — Dabber43 · 2026-08-18
- Hands-on NVIDIA DGX Spark: Running Local Agents 24/7 — heyshrutimishra · 2026-08-18
- New Book: CPU and GPU Internals Explained via Rust — rsasaki0109 · 2026-08-18
- Running Qwen 27B via llama.cpp RPC on old GPUs: benchmarks and tuning tips — BigPoppaK78 · 2026-08-18
- Nvidia Backs OpenAI Data Center; Anthropic Revenue Amazes — Stratechery · 2026-08-18