← back to catalog · registered 2026-08-22 13:56

mradermacher/gemma-3-12b-it-abliterated-v2-i1-GGUF

mradermacher Gemma 12B GGUF second-order 131K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2Fgemma-3-12b-it-abliterated-v2-i1-GGUF"
Response includes
  • classification m8
  • files 27
  • benchmarks 11 entries
  • hub_downloads_all_time 11,127
  • author_summary 3324 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
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='mlabonne/gemma-3-12b-it-abliterated-v2' (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.

What is a refusal direction? →
Downloads · lifetime
11K
792 last 30d - cooling
Likes
3
Model age
16mo ago
created 2025-05-30
Downloads over time
Now11.4K→from781↑1,354%
04.2K8.3K12.5K781 on May 28, 202511.4K on Oct 11May '25Aug '25Nov '25FebMayAug
May 28, 2025 → Oct 11 · 112 snapshots · spans 501 days

Benchmarks

Benchmark Score Source
Entertainment 0.8 UGI
Hazardous 0.6 UGI
Natural Intelligence 8.16 UGI
Political lean -5.3% UGI
Sensitive-Info 8.74 UGI
SocPol 1.2 UGI
UGI 28.33 UGI
Willingness (10) 6.8 UGI
W10-Adherence 6.5 UGI
W10-Direct 7 UGI
Writing NA UGI

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 · 1K 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 en base_model:mlabonne/gemma-3-12b-it-abliterated-v2 base_model:quantized:mlabonne/gemma-3-12b-it-abliterated-v2 license:gemma endpoints_compatible region:us imatrix conversational

Related

Total size
129 GB
Files
27
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2025-05-30 08:00

Files by quantization

Q6_K 1 file 9.00 GB
gemma-3-12b-it-abliterated-v2.i1-Q6_K.gguf 9.00 GB b1d99f10 download
Q5_K 2 files 15.5 GB
gemma-3-12b-it-abliterated-v2.i1-Q5_K_M.gguf 7.87 GB 43808be7 download
gemma-3-12b-it-abliterated-v2.i1-Q5_K_S.gguf 7.67 GB b886d27e download
Q4 2 files 13.5 GB
gemma-3-12b-it-abliterated-v2.i1-Q4_1.gguf 7.04 GB 0eaecfa2 download
gemma-3-12b-it-abliterated-v2.i1-Q4_0.gguf 6.43 GB 03fd83f7 download
Q4_K 2 files 13.3 GB
gemma-3-12b-it-abliterated-v2.i1-Q4_K_M.gguf 6.80 GB 82b0edff download
gemma-3-12b-it-abliterated-v2.i1-Q4_K_S.gguf 6.46 GB dc435be6 download
IQ4 2 files 12.5 GB
gemma-3-12b-it-abliterated-v2.i1-IQ4_NL.gguf 6.41 GB ce725836 download
gemma-3-12b-it-abliterated-v2.i1-IQ4_XS.gguf 6.10 GB 5044ae58 download
Q3_K 3 files 16.7 GB
gemma-3-12b-it-abliterated-v2.i1-Q3_K_L.gguf 6.04 GB f6a7ca20 download
gemma-3-12b-it-abliterated-v2.i1-Q3_K_M.gguf 5.60 GB f6e4928c download
gemma-3-12b-it-abliterated-v2.i1-Q3_K_S.gguf 5.08 GB 11a7cab2 download
IQ3 4 files 19.7 GB
gemma-3-12b-it-abliterated-v2.i1-IQ3_M.gguf 5.27 GB ddfe5188 download
gemma-3-12b-it-abliterated-v2.i1-IQ3_S.gguf 5.08 GB d55d85c7 download
gemma-3-12b-it-abliterated-v2.i1-IQ3_XS.gguf 4.85 GB 8a31d718 download
gemma-3-12b-it-abliterated-v2.i1-IQ3_XXS.gguf 4.46 GB 06942564 download
Q2_K 2 files 8.58 GB
gemma-3-12b-it-abliterated-v2.i1-Q2_K.gguf 4.44 GB 72a278ed download
gemma-3-12b-it-abliterated-v2.i1-Q2_K_S.gguf 4.14 GB d79ca917 download
IQ2 4 files 14.6 GB
gemma-3-12b-it-abliterated-v2.i1-IQ2_M.gguf 4.01 GB f5857557 download
gemma-3-12b-it-abliterated-v2.i1-IQ2_S.gguf 3.74 GB c2fb2184 download
gemma-3-12b-it-abliterated-v2.i1-IQ2_XS.gguf 3.58 GB 8f159d4c download
gemma-3-12b-it-abliterated-v2.i1-IQ2_XXS.gguf 3.28 GB 585fa44e download
IQ1 2 files 5.69 GB
gemma-3-12b-it-abliterated-v2.i1-IQ1_M.gguf 2.95 GB cb226dfc download
gemma-3-12b-it-abliterated-v2.i1-IQ1_S.gguf 2.74 GB 5bc23f61 download
Auxiliary files 3 files 7.10 MB
imatrix.dat 7.09 MB b90201c3 download
README.md 5.88 KB 5489f9df download
.gitattributes 3.42 KB 98377379 download

README current version from Hugging Face


base_model: mlabonne/gemma-3-12b-it-abliterated-v2
language:

  • en
    library_name: transformers
    license: gemma
    quantized_by: mradermacher

About

weighted/imatrix quants of https://huggingface.co/mlabonne/gemma-3-12b-it-abliterated-v2

static quants are available at https://huggingface.co/mradermacher/gemma-3-12b-it-abliterated-v2-GGUF

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 i1-IQ1_S 3.0 for the desperate
GGUF i1-IQ1_M 3.3 mostly desperate
GGUF i1-IQ2_XXS 3.6
GGUF i1-IQ2_XS 3.9
GGUF i1-IQ2_S 4.1
GGUF i1-IQ2_M 4.4
GGUF i1-Q2_K_S 4.5 very low quality
GGUF i1-Q2_K 4.9 IQ3_XXS probably better
GGUF i1-IQ3_XXS 4.9 lower quality
GGUF i1-IQ3_XS 5.3
GGUF i1-IQ3_S 5.6 beats Q3_K*
GGUF i1-Q3_K_S 5.6 IQ3_XS probably better
GGUF i1-IQ3_M 5.8
GGUF i1-Q3_K_M 6.1 IQ3_S probably better
GGUF i1-Q3_K_L 6.6 IQ3_M probably better
GGUF i1-IQ4_XS 6.7
GGUF i1-IQ4_NL 7.0 prefer IQ4_XS
GGUF i1-Q4_0 7.0 fast, low quality
GGUF i1-Q4_K_S 7.0 optimal size/speed/quality
GGUF i1-Q4_K_M 7.4 fast, recommended
GGUF i1-Q4_1 7.7
GGUF i1-Q5_K_S 8.3
GGUF i1-Q5_K_M 8.5
GGUF i1-Q6_K 9.8 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 3 versions

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

  1. 2025-05-30auto-patch README.md0c2bff55.9 KB
    Loading...
  2. 2025-05-30auto-patch README.mdc42f34c4.9 KB
    Loading...
  3. 2025-05-30uploaded from kaos09e2b8f246 B
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration