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

mradermacher/gemma-3-27b-it-abliterated-normpreserve-v1-GGUF

mradermacher Gemma 27B 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-3-27b-it-abliterated-normpreserve-v1-GGUF"
Response includes
  • classification m8
  • files 15
  • benchmarks 11 entries
  • hub_downloads_all_time 2,910
  • 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='YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1' (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
3K
535 last 30d - stable
Likes
0
Model age
10mo ago
created 2025-12-11
Downloads over time
Now3.1K→from355↑773%
2181.3K2.3K3.4K355 on Dec 10, 20253.1K on Oct 11Dec '25FebAprJunAugOct
Dec 10, 2025 → Oct 11 · 83 snapshots · spans 305 days

Benchmarks

Benchmark Score Source
Entertainment 1.8 UGI
Hazardous 2.4 UGI
Natural Intelligence 34.11 UGI
Political lean -12.4% UGI
Sensitive-Info 22.34 UGI
SocPol 2.7 UGI
UGI 36.56 UGI
Willingness (10) 6.5 UGI
W10-Adherence 5 UGI
W10-Direct 8 UGI
Writing 43.01 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.

Metadata

License
gemma
Languages
en
Quantizations
IQ4 Q2_K Q3_K Q4_K Q5_K Q6_K Q8_0
Tags
transformers gguf en base_model:YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1 base_model:quantized:YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1 license:gemma endpoints_compatible region:us conversational

Related

Total size
174 GB
Files
15
Quantizations
9
Registered
2026-08-22 13:56
Last updated on HF
2025-12-11 10:35

Files by quantization

Q8_0 2 files 27.3 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q8_0.gguf 26.7 GB c80c50c4 download
gemma-3-27b-it-abliterated-normpreserve-v1.mmproj-Q8_0.gguf 570 MB acd9fe34 download
Q6_K 1 file 20.6 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q6_K.gguf 20.6 GB 7a9ecfaf download
Q5_K 2 files 35.4 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q5_K_M.gguf 17.9 GB a1e2a63f download
gemma-3-27b-it-abliterated-normpreserve-v1.Q5_K_S.gguf 17.5 GB 0bf76a1e download
Q4_K 2 files 30.0 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q4_K_M.gguf 15.4 GB 4c3bc225 download
gemma-3-27b-it-abliterated-normpreserve-v1.Q4_K_S.gguf 14.6 GB d7b519e5 download
IQ4 1 file 13.9 GB
gemma-3-27b-it-abliterated-normpreserve-v1.IQ4_XS.gguf 13.9 GB ec842042 download
Q3_K 3 files 37.4 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q3_K_L.gguf 13.5 GB 2f18d57c download
gemma-3-27b-it-abliterated-normpreserve-v1.Q3_K_M.gguf 12.5 GB 6ae5efc2 download
gemma-3-27b-it-abliterated-normpreserve-v1.Q3_K_S.gguf 11.3 GB b129808d download
Q2_K 1 file 9.78 GB
gemma-3-27b-it-abliterated-normpreserve-v1.Q2_K.gguf 9.78 GB 41d19ee3 download
F16 1 file 818 MB
gemma-3-27b-it-abliterated-normpreserve-v1.mmproj-f16.gguf 818 MB b6026ce1 download
Auxiliary files 2 files 7.12 KB
README.md 4.48 KB 106c7317 download
.gitattributes 2.64 KB 9436d763 download

README current version from Hugging Face


base_model: YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1
language:

  • en
    library_name: transformers
    license: gemma
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher

About

static quants of https://huggingface.co/YanLabs/gemma-3-27b-it-abliterated-normpreserve-v1

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

weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.

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 mmproj-Q8_0 0.7 multi-modal supplement
GGUF mmproj-f16 1.0 multi-modal supplement
GGUF Q2_K 10.6
GGUF Q3_K_S 12.3
GGUF Q3_K_M 13.5 lower quality
GGUF Q3_K_L 14.6
GGUF IQ4_XS 15.0
GGUF Q4_K_S 15.8 fast, recommended
GGUF Q4_K_M 16.6 fast, recommended
GGUF Q5_K_S 18.9
GGUF Q5_K_M 19.4
GGUF Q6_K 22.3 very good quality
GGUF Q8_0 28.8 fast, best quality

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.

README history 3 versions

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

  1. 2025-12-11auto-patch README.mdc60f4ae4.5 KB
    Loading...
  2. 2025-12-11auto-patch README.mdf279aff4.1 KB
    Loading...
  3. 2025-12-11uploaded from nico1db26bd5393 B
    Loading...

Discussions 1 thread

  1. 2026-05-18Imatrix Quantsopen7 💬#1
    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