250M Parameter Model Trained on 30B Tokens Reaches 60MB Size
August 24, 2026
A custom 250M parameter model trained on 30B FineWeb tokens achieves sub-2-bit quantization for a 60MB footprint. The system runs at 400 tok/s on laptop CPUs and utilizes 1-bit compression for KV caches to support 1M token contexts.
HOW THIS AFFECTS YOU
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builderYou can deploy high-speed, long-context models on low-end edge hardware without a GPU.
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researcherThe 1-bit KV cache compression technique offers a new path for massive context scaling on limited RAM.