A 27.8-billion-parameter AI model now fits on your phone.
PrismML, a Caltech-spinout AI company backed by Khosla Ventures, Cerberus, Google, and Samsung, announced Bonsai 27B on July 14. The model runs locally on high-end mobile devices like the iPhone 17 Pro, processing roughly 11 tokens per second in its most compressed form. No cloud. No latency round-trips. Just a phone doing the heavy lifting.
How you shrink a giant model into a pocket
The trick is something called extreme low-bit quantization. PrismML reduced the precision of each parameter from 16-bit floating point down to as low as 1 bit.
A standard FP16 version of the model would occupy around 54 GB of memory. The 1-bit binary version of Bonsai 27B takes up just 3.9 GB. The 1.58-bit ternary variant sits at 5.9 GB. Despite that aggressive compression, PrismML says the model retains 90-95% of benchmark performance compared to its full-precision baseline across math, coding, reasoning, and vision tasks.
