#model-compression

LocalLLaMA liked the promise of 1.58-bit models, but the thread quickly asked the hard question: are the comparisons fair against quantized Qwen peers, or just full-precision baselines?

A well-received r/LocalLLaMA post spotlighted PrismML’s 1-bit Bonsai launch, which claims to shrink an 8.2B model to 1.15GB with an end-to-end 1-bit design. The pitch is not just compression, but practical on-device throughput and energy efficiency.