Bonsai 27B field guide
How large is Ternary Bonsai 27B?
A clear comparison of ideal, GGUF, and MLX sizes for Ternary Bonsai 27B, including optional vision and speculative decoding files.
How much storage and memory does Ternary Bonsai 27B use?
PrismML reports three useful size figures. The ideal ternary language representation is about 5.9 GB. The deployed GGUF language model is about 7.2 GB. The current MLX safetensors bundle is 8.49 GB and includes the vision tower. Runtime memory rises above file size when you add buffers and context.
Do not mix the package sizes
The 5.9 GB figure is an information based target. It assumes native ternary packing at about 1.71 bits per weight. Current kernels place each ternary value in a 2 bit slot, which raises the deployed GGUF language model to about 7.2 GB.
The MLX package stores a scale and bias for each group and includes the vision tower in the same file. PrismML reports 8.49 GB for that bundle.
Optional components
GGUF releases can add a vision projection file and a DSpark draft model. Those files serve separate jobs. Text inference only needs the language model. Vision needs the projection file. Speculative decoding needs the draft model and is not enabled by default on Apple silicon in the whitepaper tests.
Questions people ask
Why does Hugging Face show a different size?
Repository totals can include metadata, configuration files, split weights, or optional components. Check the exact artifact and runtime format.
Is disk size the same as peak memory?
No. Peak memory includes loaded weights, runtime buffers, activations, and the context cache.
Primary sources
Vendor claims on this page are labeled as PrismML claims. Local results are added only after a saved trace completes.