#bonsai

A 27B model running on phones would shift the boundary for private, offline AI. RunAnywhere says Bonsai uses 1-bit weights, fits in 3.9GB, and keeps about 90% of full-precision quality in its own evals.

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 strong r/LocalLLaMA reaction suggests PrismML’s Bonsai launch is landing as more than another compression headline. The discussion combines the company’s end-to-end 1-bit claims with early hands-on reports that the models feel materially more usable than earlier BitNet-style experiments.