PrismML releases Bonsai 27B, the first 27B-class model that runs on a phone

Bonsai 27B (1-bit LLM): The First 27B-Class Model to Run on a Phone

PrismML compressed Qwen3.6 27B to 3.9 GB, fitting it on an iPhone 17 Pro. The ternary variant (5.9 GB) retains 95% of the full-precision baseline; the 1-bit variant (3.9 GB) retains 90%. Math and coding scores barely drop, tool calling holds up, but vision tasks degrade more noticeably. Both variants are multimodal, support 262K-token context and speculative decoding, and are released under Apache 2.0. PrismML argues this lets agentic workflows run locally, eliminating per-step API costs and keeping user data on-device.

Why it matters: PrismML compressed Qwen3.6 27B to 3.9 GB running on an iPhone 17 Pro — ternary version retains 95% capability, 1-bit retains 90%, with math and coding scores nearly intact. This is a real on-device milestone, not a paper concept. Points off for significant vision degradation, ...