Ternary-Bonsai-2-27B-MLX-8bit
Stock-runtime MLX build of
Ternary-Bonsai-2-27B — prism-ml's ternarized
Qwen3.8-27B (64-layer qwen3_5 hybrid: Gated-DeltaNet + every-4th full attention, with the
official vision tower) — with the blockwise Hadamard rotation unfolded back into the standard
weight basis, so it loads in unmodified mlx-vlm (≥ 0.7): no custom runtime, no forked kernels.
8-bit affine (group 64): statistically indistinguishable from bf16 at 54% of the size.
from mlx_vlm import load, generate
model, processor = load("pipenetwork/Ternary-Bonsai-2-27B-MLX-8bit")
How this relates to prism-ml's own MLX release
prism-ml ships an excellent 8.6 GB 2-bit pack whose weights are the exact ternary
values — it is the efficiency frontier for this model, and it requires their bundled runtime
(the stored weights are Hadamard-rotated; activations are transformed to match). This set serves
the complementary case: standard-basis weights for stock tooling, fine-tuning, and downstream
conversion. The unfold is exact — refold(unfold(W)) is bitwise identical in fp32, and the fold
contract was verified against their runtime, not assumed (applying the sign vector in the wrong
order moves logits by 7.4; the test catches it).
Fidelity
Against prism's 2-bit pack running under their runtime, same prompts, 81 positions: max |Δlogit| 0.22 on a ±20 scale, cosine 0.99999, argmax 96.7–100% (the flips are ties; in fp16 — their activation dtype — agreement is 100%). Paired over 145 shared wikitext-2 windows the perplexity ratio is 0.9992 [0.9990, 0.9994]: a bf16-rounding-level difference.
Perplexity (wikitext-2 test, 296,815 tokens, identical windows through stock mlx-vlm):
| build | size | ppl |
|---|---|---|
| prism 2-bit, their runtime | 8.6 GB | 8.9607 |
| bf16 (this set's unquantized) | 54.7 GB | 8.9679 |
| 8-bit | 29.5 GB | 8.9636 |
| 6-bit | 22.8 GB | 8.9548 |
| 4-bit | 16.1 GB | 9.1497 |
8-bit and 6-bit are statistically indistinguishable from bf16; 4-bit costs +2.1% — the only
build with a measurable loss, and still the smallest stock-loadable one. Vision verified
end-to-end. Requires mlx-vlm ≥ 0.7 (earlier versions double-shift qwen3_5 norms).
License
Apache-2.0, as upstream (prism-ml/Ternary-Bonsai-2-27B-gguf); their NOTICE.txt is included. Conversion code: https://github.com/PipeNetwork/bonsai2-mlx.