---

license: apache-2.0

base_model:

- dealignai/Bonsai-2-27B-Ternary-CRACK-GGUF

- prism-ml/Ternary-Bonsai-2-27B-gguf

library_name: gguf

pipeline_tag: text-generation

tags:

- gguf

- ternary

- mtp

- speculative-decoding

- qwen3.5

- opencoti

- abliterated

- uncensored

---

Bonsai 2 27B Ternary CRACK — MTP bundle (GGUF)

dealignai's Bonsai 2 27B Ternary CRACK

(the abliterated build of PrismML's

Ternary Bonsai 2 27B)

with a NextN / MTP draft head bundled in, so the model self-speculates — no

second file, no external drafter. It is the same bundle as

ManniX-ITA/Ternary-Bonsai-2-27B-MTP-GGUF,

made from dealignai's file instead of PrismML's.

> This model does not refuse. Its refusal behaviour was removed by dealignai at

> the weight level, so it will produce content other models decline, including

> content that is offensive, unsafe, or illegal in some jurisdictions. It is

> published for adult and research use. You are responsible for what you generate

> and for complying with the law where you are; do not put it in front of other

> people without a moderation layer of your own. No warranty.

The published CRACK GGUF carries no NextN layer. This bundle adds the upstream

Qwen/Qwen3.8-27B MTP head (its mtp.*

tensors, exported by upstream llama.cpp convert_hf_to_gguf.py --mtp --outtype q8_0)

as one extra layer; every other key and tensor is dealignai's file, byte for byte.

The head stays in the normal basis (it is not among the Hadamard-rotated tensors);

its token-embedding lookup on the rotated table gets the inverse transform in the

engine.

| File | Weights | Size | sha256 |

|---|---|---|---|

| Bonsai-2-27B-PQ2_0-CRACK-MTP.gguf | PQ2_0 (ternary, 2.13 bpw packing) + q8_0 head | 7.66 GB | 6c6b6ef5a8c0eec092c42a79cfc423f2b39bb46fa1bf492d02fce85270351d5b |

Made from Bonsai-2-27B-PQ2_0-CRACK.gguf, sha256 5b24ea3eebc3e0bccd05fb474eb88b10c57699d71a5db2f29485e3789a70d55d

(dealignai's file after their re-download notice of 2026-09-18). dealignai publish

the PQ2_0 packing only, so there is no PTQ1_0 bundle.

The vision projector is not duplicated here: use PrismML's

Ternary-Bonsai-2-27B-mmproj-Q8_0.gguf or -BF16.gguf from the base repo with

--mmproj.

Running

This file needs an engine that runs ternary weights and a bundled NextN head

on a qwen35 hybrid: opencoti's llamafile

(from the c11 cut) does; PrismML's own llama.cpp fork runs the ternary weights but

not the bundled head.

./opencoti-llamafile --server -m Bonsai-2-27B-PQ2_0-CRACK-MTP.gguf \
    -ngl 99 -fa on --spec-type draft-mtp

# with image input
./opencoti-llamafile --server -m Bonsai-2-27B-PQ2_0-CRACK-MTP.gguf \
    --mmproj Ternary-Bonsai-2-27B-mmproj-Q8_0.gguf -ngl 99 -fa on --spec-type draft-mtp

Ready-made tags for xOllama

(v0.40.3-xollama or later), with and without the head and the projector:

xollama run mannix/bonsai-2-27b-crack                    # MTP + Q8_0 vision
xollama run mannix/bonsai-2-27b-crack:mtp-pq2_0          # text only, with the head

See ollama.com/mannix/Bonsai-2-27B-CRACK.

What MTP buys

Measured through xOllama 0.40.3-xollama.1 on the opencoti c11 engine, RTX 3090,

one coding prompt, temperature 0, about 600 to 640 tokens:

| File | MTP off | MTP on (depth 2) | acceptance |

|---|---|---|---|

| CRACK PQ2_0 | 46.0 tok/s | 66.2 tok/s | 0.76 at the first drafted position, 2.3 tokens / step |

| base PQ2_0, same prompt, for comparison | 45.8 tok/s | 68.7 tok/s | 0.71 |

One prompt is not a benchmark. Code is more predictable than chat: on the base

model, twelve chat prompts gave 46 to 57 tok/s on the same card, so expect between

1.25x and 1.5x depending on what you generate. Both vision projectors read a test

image correctly with this file.

Speculation preserves the model's distribution, not the argmax at near-ties: with

greedy sampling an answer can differ from the unspeculated one at a position where

the top-2 tokens are within a few hundredths of a nat.

dealignai's refusal and MMLU evaluations are on

their card;

they were not re-run for this bundle.

Reproducing the bundle

1. Export the head: convert_hf_to_gguf.py --mtp --outtype q8_0 Qwen/Qwen3.8-27B

(upstream llama.cpp) → mtp-Qwen3.8-27B-Q8_0.gguf

(c9e5c641de0c9896641c07a400ed92075024fe2c623549d427b1a6e44075bc0a), the same

head file as in the base bundles.

1. Bundle it into dealignai's GGUF with opencoti's bonsai2-mtp-bundle.py: the head

becomes layer block_count, nextn_predict_layers = 1; the script refuses unless

every shared qwen35.* hyperparameter and the vocab agree and no tensor collides.

License

Apache-2.0, as the base models and the Qwen3.8-27B head. Credits: dealignai for the

abliteration, PrismML for Bonsai 2 (created using Bonsai by Prism ML), the Qwen team

for Qwen3.8-27B.