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mradermacher/gemma-4-31B-it-abliterated-v3-i1-GGUF

mradermacher Gemma 31B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 15,352
  • 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='simonko912/gemma-4-31B-it-abliterated-v3' (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
15K
2K last 30d - stable
Likes
3
Model age
5mo ago
created 2026-04-29
Downloads over time
Now15.6K→from6.6K↑138%
3335.9K11.5K17.1K6.6K on Apr 2915.6K on Oct 11AprMayJunJulAugSepOct
Apr 29 → Oct 11 · 64 snapshots · spans 165 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 · 2K 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 abliterated uncensored gemma4 direct-weight-editing abliterix vllm llm-judge en base_model:simonko912/gemma-4-31B-it-abliterated-v3 base_model:quantized:simonko912/gemma-4-31B-it-abliterated-v3

Related

Total size
312 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-04-30 02:56

Files by quantization

Q6_K 1 file 23.5 GB
gemma-4-31B-it-abliterated-v3.i1-Q6_K.gguf 23.5 GB c5b49ad0 download
Q5_K 2 files 40.2 GB
gemma-4-31B-it-abliterated-v3.i1-Q5_K_M.gguf 20.3 GB bc1e35ea download
gemma-4-31B-it-abliterated-v3.i1-Q5_K_S.gguf 19.8 GB 45b463ec download
Q4 2 files 34.6 GB
gemma-4-31B-it-abliterated-v3.i1-Q4_1.gguf 18.1 GB 4667613a download
gemma-4-31B-it-abliterated-v3.i1-Q4_0.gguf 16.5 GB a1fd1e7b download
Q4_K 2 files 33.9 GB
gemma-4-31B-it-abliterated-v3.i1-Q4_K_M.gguf 17.4 GB 602f55fc download
gemma-4-31B-it-abliterated-v3.i1-Q4_K_S.gguf 16.5 GB d5bd4d68 download
IQ4 1 file 15.6 GB
gemma-4-31B-it-abliterated-v3.i1-IQ4_XS.gguf 15.6 GB eab98857 download
Q3_K 3 files 42.5 GB
gemma-4-31B-it-abliterated-v3.i1-Q3_K_L.gguf 15.5 GB 2346efae download
gemma-4-31B-it-abliterated-v3.i1-Q3_K_M.gguf 14.2 GB 256af3d3 download
gemma-4-31B-it-abliterated-v3.i1-Q3_K_S.gguf 12.8 GB 80618333 download
IQ3 4 files 49.7 GB
gemma-4-31B-it-abliterated-v3.i1-IQ3_M.gguf 13.4 GB 7601d722 download
gemma-4-31B-it-abliterated-v3.i1-IQ3_S.gguf 12.8 GB 46ebc5a5 download
gemma-4-31B-it-abliterated-v3.i1-IQ3_XS.gguf 12.2 GB b0b6c0d2 download
gemma-4-31B-it-abliterated-v3.i1-IQ3_XXS.gguf 11.2 GB b564e382 download
Q2_K 2 files 21.3 GB
gemma-4-31B-it-abliterated-v3.i1-Q2_K.gguf 11.1 GB 7e02cafc download
gemma-4-31B-it-abliterated-v3.i1-Q2_K_S.gguf 10.2 GB f4ebf0ce download
IQ2 4 files 36.6 GB
gemma-4-31B-it-abliterated-v3.i1-IQ2_M.gguf 10.2 GB 7e2844cd download
gemma-4-31B-it-abliterated-v3.i1-IQ2_S.gguf 9.46 GB d65933bb download
gemma-4-31B-it-abliterated-v3.i1-IQ2_XS.gguf 8.88 GB 385eb629 download
gemma-4-31B-it-abliterated-v3.i1-IQ2_XXS.gguf 8.08 GB 833a1d2f download
IQ1 2 files 13.9 GB
gemma-4-31B-it-abliterated-v3.i1-IQ1_M.gguf 7.20 GB 47d8758d download
gemma-4-31B-it-abliterated-v3.i1-IQ1_S.gguf 6.67 GB 08ae317b download
Auxiliary files 3 files 13.1 MB
gemma-4-31B-it-abliterated-v3.imatrix.gguf 13.1 MB 8bb11ce4 download
README.md 6.59 KB 40e7aa20 download
.gitattributes 3.37 KB 88a3b923 download

README current version from Hugging Face


base_model: simonko912/gemma-4-31B-it-abliterated-v3
language:

  • en
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • gemma4
  • direct-weight-editing
  • abliterix
  • vllm
  • llm-judge

About

weighted/imatrix quants of https://huggingface.co/simonko912/gemma-4-31B-it-abliterated-v3

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

static quants are available at https://huggingface.co/mradermacher/gemma-4-31B-it-abliterated-v3-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 0.1 imatrix file (for creating your own quants)
GGUF i1-IQ1_S 7.3 for the desperate
GGUF i1-IQ1_M 7.8 mostly desperate
GGUF i1-IQ2_XXS 8.8
GGUF i1-IQ2_XS 9.6
GGUF i1-IQ2_S 10.3
GGUF i1-IQ2_M 11.0
GGUF i1-Q2_K_S 11.1 very low quality
GGUF i1-Q2_K 12.0 IQ3_XXS probably better
GGUF i1-IQ3_XXS 12.2 lower quality
GGUF i1-IQ3_XS 13.2
GGUF i1-IQ3_S 13.9 beats Q3_K*
GGUF i1-Q3_K_S 13.9 IQ3_XS probably better
GGUF i1-IQ3_M 14.5
GGUF i1-Q3_K_M 15.4 IQ3_S probably better
GGUF i1-Q3_K_L 16.7 IQ3_M probably better
GGUF i1-IQ4_XS 16.8
GGUF i1-Q4_0 17.8 fast, low quality
GGUF i1-Q4_K_S 17.9 optimal size/speed/quality
GGUF i1-Q4_K_M 18.8 fast, recommended
GGUF i1-Q4_1 19.6
GGUF i1-Q5_K_S 21.4
GGUF i1-Q5_K_M 21.9
GGUF i1-Q6_K 25.3 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. 2026-04-30auto-patch README.md6e684236.6 KB
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  2. 2026-04-30auto-patch README.mda152abf4.2 KB
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  3. 2026-04-29auto-patch README.mda388d3a2.6 KB
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  4. 2026-04-29uploaded from nico1286dd3b487 B
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