---

license: apache-2.0

license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE

library_name: gguf

base_model: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-GGUF

base_model_relation: quantized

model_name: Qwen3.6-27B-Heretic-Cerebellum-GGUF

model_creator: Qwen

model_type: qwen3

quantized_by: deucebucket

pipeline_tag: image-text-to-text

tags:

- GGUF

- qwen3

- qwen

- quantized

- cerebellum

- imatrix

- hybrid-ssm

- mixed-precision

- 2-bit

- heretic

- uncensored

- abliterated

model-index:

• name: Qwen3.6-27B-Heretic-Cerebellum-GGUF

results:

- task:

name: Text Generation

type: text-generation

dataset:

name: AI2 Reasoning Challenge

type: ai2_arc

config: ARC-Challenge

split: test

metrics:

- name: normalized accuracy

type: acc_norm

value: 0.9690

source:

name: Local audited benchmark run (RTX 3090, llama.cpp)

url: https://huggingface.co/deucebucket/Qwen3.6-27B-Heretic-Cerebellum-GGUF/tree/main/benchmark_results

- task:

name: Text Generation

type: text-generation

dataset:

name: HellaSwag

type: hellaswag

split: validation

metrics:

- name: accuracy

type: acc

value: 0.9350

source:

name: Local audited benchmark run (RTX 3090, llama.cpp)

url: https://huggingface.co/deucebucket/Qwen3.6-27B-Heretic-Cerebellum-GGUF/tree/main/benchmark_results

- task:

name: Text Generation

type: text-generation

dataset:

name: MMLU-Redux

type: cais/mmlu

config: all

split: test

metrics:

- name: accuracy

type: acc

value: 0.7800

source:

name: Local audited benchmark run (RTX 3090, llama.cpp)

url: https://huggingface.co/deucebucket/Qwen3.6-27B-Heretic-Cerebellum-GGUF/tree/main/benchmark_results

- task:

name: Text Generation

type: text-generation

dataset:

name: HumanEval+ (pass@1)

type: openai_humaneval

split: test

metrics:

- name: pass@1

type: pass@1

value: 0.8537

source:

name: Local audited benchmark run (RTX 3090, llama.cpp) — chat no-think harness

url: https://huggingface.co/deucebucket/Qwen3.6-27B-Heretic-Cerebellum-GGUF/tree/main/benchmark_results

- task:

name: Text Generation

type: text-generation

dataset:

name: WikiText-2 Perplexity

type: wikitext

config: wikitext-2-raw-v1

split: test

metrics:

- name: perplexity

type: perplexity

value: 7.5624

source:

name: Local audited benchmark run (RTX 3090, llama.cpp)

url: https://huggingface.co/deucebucket/Qwen3.6-27B-Heretic-Cerebellum-GGUF/tree/main/benchmark_results

---

<p align="center">

<img src="cerebellum_banner.png" alt="Cerebellum" width="640">

</p>

Qwen 3.6 27B Heretic — Cerebellum GGUF

Sensitivity-guided mixed-precision quantization of

llmfan46/Qwen3.6-27B-uncensored-heretic-v2-GGUF,

which is itself a decensored variant of

Qwen/Qwen3.6-27B

produced by llmfan46 using Heretic v1.2.0.

All future Heretic versions of this build will live in this repository.

Version identifiers appear only in filenames, not in the repo name.

Files

| File | Size | Description |

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

| Qwen3.6-27B-Heretic-Cerebellum-v2-Q2_K_Mixed.gguf | 13.33 GB (13,330,582,624 bytes) | Cerebellum v5 (qkvfix) recipe — higher task scores |

| Qwen3.6-27B-Heretic-Cerebellum-v1-Q2_K_Mixed.gguf | 12.87 GB (12,866,587,680 bytes) | Cerebellum v4 recipe — smaller file |

| Qwen3.6-27B-mmproj-BF16.gguf | ~888 MB (931,146,048 bytes) | Vision projector, passed through unmodified from llmfan46's repo |

The vision projector is required for multimodal (image/video) use.

It is identical to the file distributed by llmfan46 and is included here

for single-repo convenience only.

Provenance

1. Base architecture: Qwen/Qwen3.6-27B — Qwen Team (Apache-2.0)
2. Heretic variant: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-GGUF — llmfan46.

The BF16 GGUF from that repository was used as the direct quantization source.

llmfan46 applied Heretic v1.2.0 with the Magnitude-Preserving Orthogonal

Ablation (MPOA) method, targeting attn.o_proj, attn.out_proj, and

mlp.down_proj. Their reported result: 0.0021 KL divergence from base,

6/100 refusals vs 92/100 on the original model, MMLU accuracy 85.61%

vs 86.65% on the original.

1. Quantization: the Cerebellum override map is transferred verbatim onto the

heretic source (no re-ablation), with the coder imatrix (ncall=8).

- v2 uses the v5 (qkvfix) recipe — a 232-entry override holding

attn_qkv at q5_K/q6_K/q8_0 (the coding-critical attention pathway),

matching the stock Qwen3.6-27B Cerebellum v5 build.

- v1 uses the earlier v4 recipe (181-entry override).

Benchmarks

Benchmarks run on these GGUF files directly using llama.cpp on RTX 3090.

All numbers are audited; every failed answer was manually verified as a genuine

model error — audit reports are in benchmark_results/AUDIT_*.md.

Full per-question detail (summary JSON, samples JSONL, EvalPlus eval JSON,

adversarial audit reports) is in benchmark_results/ in this repository.

Heretic Cerebellum v2 vs v1 (same source, same harness)

Both builds measured directly on their GGUF files with llama.cpp llama-server

on an RTX 3090, temperature 0, no-thinking. v2 measured 2026-06-22, v1 2026-06-11.

HumanEval/HumanEval+ use the chat-completions harness

(scripts/benchmark_evalplus_chat.py, enable_thinking: false,

thinking_budget_tokens: 0, BENCH_WORKERS=1); ARC/HellaSwag/MMLU at 4 workers.

| Benchmark | Heretic v2 (13.33 GB) | Heretic v1 (12.87 GB) |

|-----------|:---:|:---:|

| ARC-Challenge (1172 q) | 96.9% | 96.9% |

| HellaSwag (10042 q) | 93.5% | 90.1% |

| MMLU-Redux (2400 q) | 78.0% | 76.2% |

| HumanEval base (chat, no-think) | 90.2% | 89.6% |

| HumanEval+ (chat, no-think) | 85.4% | 84.8% |

| Wiki PPL (wikitext-2-raw test) | 7.56 | 6.93 |

What changed in v2: the v5 (qkvfix) override holds attn_qkv at q5_K/q6_K/q8_0

rather than the v4 allocation. Versus v1 that moves HellaSwag +3.4, MMLU-Redux

+1.8, HumanEval base/plus +0.6/+0.6, ARC unchanged, at a cost of +0.46 GB and

+0.64 Wiki PPL (coder-imatrix calibration plus the abliteration shift; PPL is a

sanity check, not a quality gate). The v2 HumanEval run audited clean: 0/164

give-ups, all real attempts. Pick v1 for the smallest file, v2 for higher scores.

Heretic Abliteration Details (from llmfan46)

The following parameters are as reported in llmfan46's model card and are

reproduced here for downstream reference.

| Parameter | Value |

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

| direction_index | 30.38 |

| attn.out_proj.max_weight | 1.58 |

| attn.out_proj.max_weight_position | 38.93 |

| attn.out_proj.min_weight | 1.51 |

| attn.out_proj.min_weight_distance | 32.78 |

| mlp.down_proj.max_weight | 1.80 |

| mlp.down_proj.max_weight_position | 41.28 |

| mlp.down_proj.min_weight | 0.54 |

| mlp.down_proj.min_weight_distance | 43.66 |

| attn.o_proj.max_weight | 1.99 |

| attn.o_proj.max_weight_position | 48.06 |

| attn.o_proj.min_weight | 1.75 |

| attn.o_proj.min_weight_distance | 39.00 |

Targeted components: attn.o_proj, attn.out_proj, mlp.down_proj.

Tool: Heretic v1.2.0,

method: Magnitude-Preserving Orthogonal Ablation (MPOA)

(reference).

Cerebellum Tensor Allocation

Transferred verbatim from the matching stock Qwen3.6-27B build.

v2 (v5 qkvfix): 232-entry override over a Q2_K base, with attn_qkv held high

across all blocks (q5_K ×34, q6_K ×9, q8_0 ×5) — the coding-critical attention

pathway. v1 (v4): earlier 181-entry allocation.

| Group | Precision | Rationale |

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

| SSM state parameters | F32 | Hard-fail below 4-bit — NaN with no gradual degradation |

| SSM in_proj_a/b, A_log, dt_bias, conv1d, in_proj_z | ≥ Q4 minimum | 4-bit floor enforced per hybrid SSM ablation results |

| Most-sensitive attention tensors | Q5_K / Q6_K / Q8_0 | Sacred-pinned per per-tensor PPL ablation |

| Norm tensors | F32 | Protected; standard practice |

| Bulk ffn / remaining attention | Q2_K | Base precision, imatrix-guided |

Protected: all norms (F32), SSM recurrent state (F32).

Perplexity Note

Wiki PPL is reported as a sanity check, not a quality gate. v2 (7.56) is higher

than v1 (6.93): the v2 build uses the coder imatrix (which optimizes for code and

shifts wiki-text PPL) on top of the abliteration's distributional shift. v2's task

benchmarks above are higher than v1's across HellaSwag, MMLU, and HumanEval, which

is the divergence PPL cannot see.

Measured launch (RTX 3090, llama.cpp)

Measured 2026-06-13 on a single RTX 3090 (24 GB), one llama-server, KV cache q8_0:

| metric | measured |

|---|---|

| decode speed | 36.5 tok/s |

| peak VRAM (4-slot serving) | 16.2 GB |

| max measured context (q8_0 KV) | 131,072 |

llama-server -m Qwen3.6-27B-Heretic-Cerebellum-v2-Q2_K_Mixed.gguf \
  -ngl 99 --parallel 4 -c 24576 --jinja

_This rig's measurements; no quality claims beyond them._

Runtime — Casual Deployment

llama-server \
  --model Qwen3.6-27B-Heretic-Cerebellum-v2-Q2_K_Mixed.gguf \
  --mmproj Qwen3.6-27B-mmproj-BF16.gguf \
  --n-gpu-layers 99 \
  --ctx-size 8192 \
  --jinja

--jinja is required for Qwen3.6. The enable_thinking chat-template flag

only takes effect when the Jinja template path is active; without it, the

model defaults to thinking mode on every request.

Non-thinking requests require an explicit flag at the API level:

{"chat_template_kwargs": {"enable_thinking": false}}

Qwen3.6 does not support the /think and /nothink soft-switch tokens

used by Qwen3.5. Thinking mode is on by default.

Recommended Sampling Parameters

From the official Qwen3.6-27B documentation.

| Mode | temperature | top_p | top_k | min_p | presence_penalty | repetition_penalty |

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

| Thinking — general | 1.0 | 0.95 | 20 | 0.0 | 1.5 | 1.0 |

| Thinking — precise coding (WebDev) | 0.6 | 0.95 | 20 | 0.0 | 0.0 | 1.0 |

| Non-thinking (instruct) | 0.7 | 0.80 | 20 | 0.0 | 1.5 | 1.0 |

presence_penalty can be adjusted between 0 and 2 to reduce repetition loops;

higher values may occasionally cause language mixing.

Reproduction

Standard Cerebellum recipe. The tensor-type override file and ablation logs

from the stock v4 build apply directly.

# 1. imatrix (constant ~300 MB RAM)
python -m osmosis.imatrix_stream \
    --model Qwen3.6-27B-uncensored-heretic-v2-BF16.gguf \
    --output imatrix.dat

# 2. quantize with stock llama-quantize
llama-quantize \
    --imatrix imatrix.dat \
    --tensor-type-file cerebellum_v5_qkvfix_overrides.txt \
    Qwen3.6-27B-uncensored-heretic-v2-BF16.gguf \
    Qwen3.6-27B-Heretic-Cerebellum-v2-Q2_K_Mixed.gguf \
    Q2_K

The imatrix used for this build was generated from the coder corpus

(ncall=8; same corpus as the stock Cerebellum v4 build).

The v5 (232-entry) and v4 (181-entry) tensor override files are included

in this repository alongside the ablation logs.

Benchmark Artifacts

Summary JSONs, per-question JSONL samples, EvalPlus eval JSON files, and

adversarial audit reports (AUDIT_*.md) are in benchmark_results/ in this

repository per project policy.

Credits

• Base model: Qwen/Qwen3.6-27B — Qwen Team
• Heretic variant and BF16 source: llmfan46/Qwen3.6-27B-uncensored-heretic-v2-GGUF — llmfan46
• Abliteration tool: Heretic v1.2.0 by p-e-w
• GGUF runtime: llama.cpp
• Quantization method and workflow: Cerebellum — deucebucket