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AtticusG3/Qwopus3.6-27B-Fusion-heretic-MTP-GGUF

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Model Card

Qwopus3.6-27B-Fusion-heretic-MTP (GGUF)

Imatrix-guided GGUF quants of KyleHessling1/Qwopus3.6-27B-Fusion-BF16 after [Heretic](https://github.com/p-e-w/heretic) abliteration, with MTP / NextN heads preserved.

Base model credit: Fusion is Kyle Hessling’s reasoning⊕coding merge of Qwen3.6-27B lineage. This repo only adds Heretic abliteration + GGUF packaging. See the Fusion BF16 card for merge method, benchmarks, and intended use.

Files

FileQuantApprox. sizeNotes
Qwopus3.6-27B-Fusion-heretic-MTP-F16.ggufF16~51 GBFull-precision GGUF (conversion source)
Qwopus3.6-27B-Fusion-heretic-MTP-Q8_0.ggufQ8_0~28 GBHigh-fidelity; also used as imatrix host
Qwopus3.6-27B-Fusion-heretic-MTP-Q5_K_M.ggufQ5KM~19 GBImatrix-guided; strong quality/size
Qwopus3.6-27B-Fusion-heretic-MTP-Q4_K_M.ggufQ4KM~16 GBImatrix-guided; good default on 24–32 GB GPUs

Recommendation: start with Q4_K_M or Q5_K_M. Use Q8_0 / F16 if you are re-quantizing or measuring ceiling quality.

What changed vs Fusion BF16

  1. 1.Heretic abliteration (v1.4.0) on the BF16 weights
  2. 2.200 optimization trials
  3. 3.Scorers: KeywordRate + KLDivergence
  4. 4.Eval sets: mlabonne/harmful_behaviors + mlabonne/harmless_alpaca
  5. 5.Selected trial 77: refusal keywords 89 → 3 / 100, KL divergence 0.026
  6. 6.Across trials: KL mean ≈ 0.008, max ≈ 0.073 (no trial > 0.1)
  7. 7.MTP / NextN preserved in the GGUF (blk.64 / nextn tensors bundled). Heretic’s merge-save dropped MTP safetensors; those tensors were grafted back from Fusion BF16 before convert.
  8. 8.Chat template: Fusion’s native template (not a Compat rewrite).
  9. 9.Quantization: llama.cpp convert → Q80 → imatrix (WikiText-2 calib, 100×256 chunks) → **Q4KM** and **Q5K_M** with --imatrix.
Abliteration reduces refusal behavior; it does not remove your responsibility for how you use the model. Follow applicable law and the Qwen license.

Quick start

llama.cpp

bash
./llama-server \
  -m Qwopus3.6-27B-Fusion-heretic-MTP-Q4_K_M.gguf \
  -ngl 99 -c 32768 --jinja \
  --spec-type draft-mtp --spec-draft-n-max 4

LM Studio / koboldcpp / etc.

Import the .gguf of your choice. Prefer builds that understand Qwen3.6 / qwen35 and MTP speculative decoding if you want draft speedups.

OpenAI-compatible (example)

Point any OpenAI-compatible client at a llama-server / llama-swap endpoint serving one of these files. Thinking mode follows the Fusion / Qwen3.6 chat template (enable_thinking / jinja).

Model details

Parameters~27B
ArchitectureQwen3.6 / qwen35 hybrid (linear + periodic full attention)
ContextUp to 262,144 native (practical limit = VRAM + KV cache)
VisionNot included in these text GGUFs (BF16 Fusion retains vision tensors)
MTPIncluded (NextN / draft head)
LicenseQwen (see license link in YAML)

Provenance

StepSource / tool
BaseKyleHessling1/Qwopus3.6-27B-Fusion-BF16
AbliterationHeretic v1.4.0
Convert / quant / imatrixllama.cpp
UploaderAtticusG3

Limitations

  • —Smoke-tested for generation on a small LiveCodeBench prompt sample after quant; not a full re-benchmark of Fusion’s published scores.
  • —Some MTP (blk.64) tensors lacked imatrix entries and fell back to plain K-quants.
  • —Uncensored / abliterated models can produce disallowed content more readily than the stock chat model — use with care.

Acknowledgements

  • —Kyle Hessling — Fusion merge and BF16 release
  • —Qwen team — Qwen3.6-27B
  • —p-e-w / Heretic — abliteration tooling
  • —llama.cpp contributors — GGUF convert, imatrix, quantize

Citation

bibtex
@misc{qwopus36-fusion-heretic-mtp-gguf,
  title        = {Qwopus3.6-27B-Fusion-heretic-MTP GGUF},
  author       = {AtticusG3},
  year         = {2026},
  howpublished = {\url{https://huggingface.co/AtticusG3/Qwopus3.6-27B-Fusion-heretic-MTP-GGUF}},
  note         = {Heretic abliteration of KyleHessling1/Qwopus3.6-27B-Fusion-BF16; imatrix GGUF quants}
}