---
license: gemma
library_name: gguf
base_model: coder3101/gemma-4-26B-A4B-it-heretic
base_model_relation: quantized
model_name: Gemma-4-26B-A4B-it-Heretic-Cerebellum-v1.1-templatefix-GGUF
model_type: gemma4
quantized_by: deucebucket
pipeline_tag: text-generation
tags:
  - GGUF
  - gemma4
  - gemma
  - quantized
  - cerebellum
  - imatrix
  - moe
  - 3-bit
  - templatefix
model-index:
- name: Gemma-4-26B-A4B-it-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: 0.9548
    source:
      name: Local audited benchmark run (RTX 3090, llama.cpp)
      url: https://huggingface.co/deucebucket/Gemma-4-26B-A4B-it-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: 0.8349
    source:
      name: Local audited benchmark run (RTX 3090, llama.cpp)
      url: https://huggingface.co/deucebucket/Gemma-4-26B-A4B-it-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: 0.7142
    source:
      name: Local audited benchmark run (RTX 3090, llama.cpp)
      url: https://huggingface.co/deucebucket/Gemma-4-26B-A4B-it-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: 0.8963
    source:
      name: Local audited benchmark run (RTX 3090, llama.cpp), chat no-think harness, patched evalplus
      url: https://huggingface.co/deucebucket/Gemma-4-26B-A4B-it-Heretic-Cerebellum-GGUF/tree/main/benchmark_results
---

<p align="center">
  <img src="cerebellum_banner.png" alt="Cerebellum" width="640">
</p>

# Gemma 4 26B-A4B-it Heretic Cerebellum GGUF

Sensitivity-guided mixed-precision GGUF of [coder3101/gemma-4-26B-A4B-it-heretic](https://huggingface.co/coder3101/gemma-4-26B-A4B-it-heretic),
a decensored variant of [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it).
It uses the Cerebellum v6 tensor allocation transferred verbatim onto the heretic
weights. The shipped file carries Google's updated Gemma 4 chat-template metadata
(2026-05-18 state) with zero tensor changes. Versions appear in filenames, not the repo name.

## Files

| File | Description |
|------|-------------|
| `gemma-4-26B-A4B-it-heretic-cerebellum-v1.1-templatefix-Q3_K_M.gguf` | ~11 GB; v1 allocation + updated chat-template metadata |
| `gemma-4-26B-A4B-it-heretic.mmproj-f16.gguf` | vision projector (required for image/video) |

## Evaluation

Measured directly on the GGUF with llama.cpp `llama-server` on an RTX 3090,
temperature 0, project benchmark harness. The v1.1 templatefix file is metadata-only
over v1, so these describe the same weights. The comparison column is our own plain
(non-heretic) Cerebellum v6 build on the same harness, shown so the abliteration cost
is visible. Summary JSONs and per-question samples are in `benchmark_results/`.

| Benchmark | Heretic v6 alloc (11 GB) | Plain Cerebellum v6 (11 GB) |
|-----------|:---:|:---:|
| ARC-Challenge (1172 q) | 95.48% | 95.56% |
| HellaSwag (10042 q) | 83.49% | 84.55% |
| MMLU-Redux (2400 q) | 71.42% | 71.33% |
| HumanEval base (chat, no-think) | 92.07% | pending re-audit |
| HumanEval+ (chat, no-think) | 89.63% | pending re-audit |
| Vision smoke | 6/6 | — |

HumanEval/HumanEval+ used the chat-completions harness
(`scripts/benchmark_evalplus_chat.py`, `enable_thinking: false`,
`thinking_budget_tokens: 0`, `BENCH_WORKERS=1`, `max_tokens: 768`). The completion
audit for that run recorded 0 prompt echoes, 0 repeated function definitions,
0 pass-only outputs, and 2 genuine syntax failures. The plain v6 HumanEval artifacts
were raw-completions and are marked for re-audit, so no plain-v6 HumanEval is published.

## Usage

Gemma 4 requires `--jinja`. For non-thinking output, pass request-level
`chat_template_kwargs: {"enable_thinking": false}` and `thinking_budget_tokens: 0`;
do not set a fixed server `--reasoning-budget` (it can burn output into hidden
reasoning until the length cap, which looks like a repetition loop).

```bash
llama-server \
  --model gemma-4-26B-A4B-it-heretic-cerebellum-v1.1-templatefix-Q3_K_M.gguf \
  --mmproj gemma-4-26B-A4B-it-heretic.mmproj-f16.gguf \
  -ngl 99 --ctx-size 65536 --parallel 1 --flash-attn on \
  --cache-type-k q8_0 --cache-type-v q8_0 --jinja --reasoning auto
```

Measured on one RTX 3090 (24 GB), KV q8_0: context to 131,072. This rig's
measurements; no quality claims beyond them.

## Provenance

- Source (heretic): [coder3101/gemma-4-26B-A4B-it-heretic](https://huggingface.co/coder3101/gemma-4-26B-A4B-it-heretic) — abliterated variant
- Original family: [google/gemma-4-26B-A4B-it](https://huggingface.co/google/gemma-4-26B-A4B-it) — Google Gemma Team
- Recipe: Cerebellum v6 tensor allocation transferred to the matching heretic layout;
  v1.1 is a chat-template metadata refresh (Google 2026-05-18 template), zero tensor changes

## Credits

- Source model: `coder3101/gemma-4-26B-A4B-it-heretic`
- Original Gemma family: Google Gemma Team
- GGUF runtime: [llama.cpp](https://github.com/ggml-org/llama.cpp)
- Quantization method: [Cerebellum](https://github.com/deucebucket/cerebellum) — deucebucket