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mradermacher/gemma-4-26B-A4B-it-abliterated-i1-GGUF

mradermacher Gemma 26B GGUF MoE second-order 262K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 20,666
  • author_summary 3324 models
  • readme_text full
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Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 3 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • author=mradermacher (M8 quantization producer, never originator)
  • is_gguf=1
  • base_model='WWTCyberLab/gemma-4-26B-A4B-it-abliterated' (base has 'abliterated' marker, assume M1 default)
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
21K
2K last 30d - stable
Likes
3
Model age
6mo ago
created 2026-04-11
Downloads over time
Now21.4K→from14.7K↑46%
14.3K16.9K19.5K22K14.7K on Apr 1521.4K on Oct 12AprMayJunJulAugSepOct
Apr 15 → Oct 12 · 66 snapshots · spans 180 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 5K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
gemma
Languages
en
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf abliteration safety-research alignment gemma4 moe en base_model:WWTCyberLab/gemma-4-26B-A4B-it-abliterated base_model:quantized:WWTCyberLab/gemma-4-26B-A4B-it-abliterated license:gemma endpoints_compatible

Related

Total size
280 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-04-11 13:00

Files by quantization

Q6_K 1 file 21.1 GB
gemma-4-26B-A4B-it-abliterated.i1-Q6_K.gguf 21.1 GB 2db51041 download
Q5_K 2 files 34.6 GB
gemma-4-26B-A4B-it-abliterated.i1-Q5_K_M.gguf 17.8 GB 8bb9982e download
gemma-4-26B-A4B-it-abliterated.i1-Q5_K_S.gguf 16.8 GB 3725cd96 download
Q4_K 2 files 30.0 GB
gemma-4-26B-A4B-it-abliterated.i1-Q4_K_M.gguf 15.6 GB 06fe9f93 download
gemma-4-26B-A4B-it-abliterated.i1-Q4_K_S.gguf 14.4 GB ae5442fd download
Q4 2 files 28.4 GB
gemma-4-26B-A4B-it-abliterated.i1-Q4_1.gguf 14.9 GB 3b485ed4 download
gemma-4-26B-A4B-it-abliterated.i1-Q4_0.gguf 13.5 GB 6c0b8579 download
IQ4 1 file 13.0 GB
gemma-4-26B-A4B-it-abliterated.i1-IQ4_XS.gguf 13.0 GB e4775773 download
Q3_K 3 files 36.6 GB
gemma-4-26B-A4B-it-abliterated.i1-Q3_K_L.gguf 12.9 GB d310f258 download
gemma-4-26B-A4B-it-abliterated.i1-Q3_K_M.gguf 12.4 GB 411dba39 download
gemma-4-26B-A4B-it-abliterated.i1-Q3_K_S.gguf 11.4 GB d6ab28c8 download
IQ3 4 files 44.3 GB
gemma-4-26B-A4B-it-abliterated.i1-IQ3_M.gguf 11.5 GB 7242b089 download
gemma-4-26B-A4B-it-abliterated.i1-IQ3_S.gguf 11.4 GB 4865d755 download
gemma-4-26B-A4B-it-abliterated.i1-IQ3_XS.gguf 10.8 GB 537368da download
gemma-4-26B-A4B-it-abliterated.i1-IQ3_XXS.gguf 10.5 GB a57bf906 download
Q2_K 2 files 19.8 GB
gemma-4-26B-A4B-it-abliterated.i1-Q2_K_S.gguf 9.89 GB b7e3b1e7 download
gemma-4-26B-A4B-it-abliterated.i1-Q2_K.gguf 9.86 GB 0cedebc4 download
IQ2 4 files 36.7 GB
gemma-4-26B-A4B-it-abliterated.i1-IQ2_M.gguf 9.66 GB f750ab3b download
gemma-4-26B-A4B-it-abliterated.i1-IQ2_S.gguf 9.20 GB 9ffae4a8 download
gemma-4-26B-A4B-it-abliterated.i1-IQ2_XS.gguf 9.14 GB 456d79a8 download
gemma-4-26B-A4B-it-abliterated.i1-IQ2_XXS.gguf 8.66 GB 006abb01 download
IQ1 2 files 15.8 GB
gemma-4-26B-A4B-it-abliterated.i1-IQ1_M.gguf 8.07 GB 801e866d download
gemma-4-26B-A4B-it-abliterated.i1-IQ1_S.gguf 7.72 GB a4a31d88 download
Auxiliary files 3 files 54.3 MB
gemma-4-26B-A4B-it-abliterated.imatrix.gguf 54.3 MB 6caeff0e download
README.md 6.61 KB 5bd65ba3 download
.gitattributes 3.39 KB 08b93645 download

README current version from Hugging Face


base_model: WWTCyberLab/gemma-4-26B-A4B-it-abliterated
language:

  • en
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliteration
  • safety-research
  • alignment
  • gemma4
  • moe

About

weighted/imatrix quants of https://huggingface.co/WWTCyberLab/gemma-4-26B-A4B-it-abliterated

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/gemma-4-26B-A4B-it-abliterated-GGUF

This is a vision model - mmproj files (if any) will be in the static repository.

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs
for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF imatrix 0.2 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 8.4 for the desperate
GGUF i1-IQ1_M 8.8 mostly desperate
GGUF i1-IQ2_XXS 9.4
GGUF i1-IQ2_XS 9.9
GGUF i1-IQ2_S 10.0
GGUF i1-IQ2_M 10.5
GGUF i1-Q2_K 10.7 IQ3_XXS probably better
GGUF i1-Q2_K_S 10.7 very low quality
GGUF i1-IQ3_XXS 11.4 lower quality
GGUF i1-IQ3_XS 11.7
GGUF i1-IQ3_S 12.3 beats Q3_K*
GGUF i1-Q3_K_S 12.3 IQ3_XS probably better
GGUF i1-IQ3_M 12.5
GGUF i1-Q3_K_M 13.4 IQ3_S probably better
GGUF i1-Q3_K_L 13.9 IQ3_M probably better
GGUF i1-IQ4_XS 14.0
GGUF i1-Q4_0 14.6 fast, low quality
GGUF i1-Q4_K_S 15.6 optimal size/speed/quality
GGUF i1-Q4_1 16.1
GGUF i1-Q4_K_M 16.9 fast, recommended
GGUF i1-Q5_K_S 18.1
GGUF i1-Q5_K_M 19.2
GGUF i1-Q6_K 22.7 practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.

README history 4 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-04-11auto-patch README.md1d248926.6 KB
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  2. 2026-04-11auto-patch README.md01cbe785.4 KB
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  3. 2026-04-11auto-patch README.mdbb195c93.5 KB
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  4. 2026-04-11uploaded from nico12596971489 B
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