REDDIT · REDDIT// 11d agoMODEL RELEASE

1-bit Bonsai 8B hits 65.7 MMLU

Prism ML's 1-bit Bonsai 8B is a true 1-bit model based on the Qwen 3 architecture, achieving a 65.7 MMLU-R score with a 1.15GB footprint. By utilizing binary weights and grouped scaling, it delivers up to 6x faster inference and 80% lower energy consumption than full-precision models.

// ANALYSIS

True 1-bit quantization (binary weights) compresses the model to 1.15GB, making 8B-parameter intelligence viable for smartphones and edge hardware.

–The 65.7 MMLU-R score highlights an impressive "Intelligence Density," though it still trails Llama 3.1 8B's 72.9 score.
–Custom dequantization kernels enable 6.2x faster inference on consumer hardware like the RTX 4090.
–Current adoption is limited by the requirement for specialized forks of llama.cpp and custom runtime environments.
–The model's success suggests that binary weight optimization may eventually outpace ternary (1.58-bit) quantization for edge deployment.

// TAGS

llminferenceedge-aiopen-sourcebenchmark1-bit-bonsai-8b

DISCOVERED

11d ago

2026-04-01

PUBLISHED

11d ago

2026-03-31

RELEVANCE

9/ 10

AUTHOR

OmarBessa