low-memory

A developer created a 250M parameter quantized LLM from scratch, trained on 30B tokens, deployable in 60 MB on CPU with a novel disk-based long context system supporting up to 100M tokens.

TurboFieldfare is an open-source Swift+Metal runtime that runs the Gemma 4 26B-A4B model on Apple Silicon Macs using only ~2GB of RAM by streaming experts from SSD, enabling inference on 8GB machines.

Slater is a low-memory graph database for read-heavy workloads that serves large graphs from disk using a fixed cache budget, enabling query of hundreds of millions of nodes and billions of edges from just a few hundred MB of RAM, with standard Bolt protocol compatibility and live writes.

A port of Colibri streaming to work with Hy3, enabling the model to run on as little as 10GB of RAM/VRAM instead of the original 25GB.

A new model enables generating 3D models from a single image locally on Apple Silicon devices and iPhones, using less than 2GB RAM and completing in under 20 seconds.

A hand-crafted 5x5 pixel font optimized for 8-bit microcontrollers and tiny OLED screens, fitting in just 350 bytes.