PrismML Releases Bonsai 27B: First 27B-Class Model to Run on iPhone

PrismML

Models / LLM official + media 2 src. ~1 min

PrismML announced Bonsai 27B on July 14 — a heavily quantized derivative of Qwen3.6 27B designed to run on consumer hardware including iPhone 17 Pro. Ternary variant: 5.9 GB, 95% benchmark retention, up to 134 tok/s on RTX 5090 / 58 tok/s on M5 Max. 1-bit variant: 3.9 GB, 90% benchmark retention, 163 tok/s on RTX 5090. The model is multimodal, supports tool use and agentic workflows, and runs natively via MLX on Apple Silicon and CUDA on NVIDIA. Weights are Apache 2.0 on HuggingFace.

Why it matters

Fitting a 27B-class model with tool-calling and reasoning into 3.9 GB changes the economics of local inference for mobile and edge deployments. Developers can now run a frontier-tier base model without cloud round-trips at zero per-call cost.

Importance: 3/5

First 27B-class model fitting on iPhone; tool-calling + agentic workflows on-device; Apache 2.0; confirmed by official prismml.com + 9to5Mac

on-device mobile quantization open-source inference edge-ai apple-silicon

Sources

official PrismML — Announcing Bonsai 27B

media PrismML releases Bonsai 27B, claiming first major AI model of its size fit for iPhone — 9to5Mac