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mradermacher/Qwen3.6-27B-abliterated-v2-i1-GGUF

mradermacher Qwen 27B GGUF second-order 262K ctx
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Response includes
  • classification m8
  • files 26
  • hub_downloads_all_time 8,904
  • author_summary 3328 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='wangzhang/Qwen3.6-27B-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
9K
2K last 30d - stable
Likes
0
Model age
5mo ago
created 2026-05-08
Downloads over time
Now9.4K→from2.2K↑333%
1.8K4.6K7.4K10.1K2.2K on May 69.4K on Oct 12MayJunJulAugSepOct
May 6 → Oct 12 · 63 snapshots · spans 159 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
apache-2.0
Languages
en zh
Quantizations
IQ1 IQ2 IQ3 IQ4 Q2_K Q3_K Q4 Q4_K Q5_K Q6_K
Tags
transformers gguf abliterated uncensored dense qwen3.6 hybrid-attention gated-deltanet vlm lora-search-merged-release abliterix deeprefusal-peel

Related

Total size
280 GB
Files
26
Quantizations
11
Registered
2026-08-22 13:56
Last updated on HF
2026-08-29 22:57

Files by quantization

Q6_K 1 file 20.6 GB
Qwen3.6-27B-abliterated-v2.i1-Q6_K.gguf 20.6 GB ed153e92 download
Q5_K 2 files 35.3 GB
Qwen3.6-27B-abliterated-v2.i1-Q5_K_M.gguf 17.9 GB ae615946 download
Qwen3.6-27B-abliterated-v2.i1-Q5_K_S.gguf 17.4 GB b827fecb download
Q4 2 files 30.4 GB
Qwen3.6-27B-abliterated-v2.i1-Q4_1.gguf 15.9 GB b50af6e8 download
Qwen3.6-27B-abliterated-v2.i1-Q4_0.gguf 14.5 GB 577ddf00 download
Q4_K 2 files 29.9 GB
Qwen3.6-27B-abliterated-v2.i1-Q4_K_M.gguf 15.4 GB 4f5bb8c6 download
Qwen3.6-27B-abliterated-v2.i1-Q4_K_S.gguf 14.5 GB 14b4f11e download
IQ4 1 file 14.0 GB
Qwen3.6-27B-abliterated-v2.i1-IQ4_XS.gguf 14.0 GB eb530584 download
Q3_K 3 files 37.0 GB
Qwen3.6-27B-abliterated-v2.i1-Q3_K_L.gguf 13.4 GB a79b297d download
Qwen3.6-27B-abliterated-v2.i1-Q3_K_M.gguf 12.4 GB d42ab27b download
Qwen3.6-27B-abliterated-v2.i1-Q3_K_S.gguf 11.2 GB 8887ad14 download
IQ3 4 files 44.8 GB
Qwen3.6-27B-abliterated-v2.i1-IQ3_M.gguf 11.7 GB 79da0194 download
Qwen3.6-27B-abliterated-v2.i1-IQ3_S.gguf 11.6 GB ad5f6f23 download
Qwen3.6-27B-abliterated-v2.i1-IQ3_XS.gguf 11.1 GB a5f0503e download
Qwen3.6-27B-abliterated-v2.i1-IQ3_XXS.gguf 10.4 GB dc150a04 download
Q2_K 2 files 19.5 GB
Qwen3.6-27B-abliterated-v2.i1-Q2_K.gguf 9.98 GB 2641889a download
Qwen3.6-27B-abliterated-v2.i1-Q2_K_S.gguf 9.54 GB 4b94d3ab download
IQ2 4 files 34.4 GB
Qwen3.6-27B-abliterated-v2.i1-IQ2_M.gguf 9.32 GB ce298059 download
Qwen3.6-27B-abliterated-v2.i1-IQ2_S.gguf 8.72 GB 719f6c21 download
Qwen3.6-27B-abliterated-v2.i1-IQ2_XS.gguf 8.47 GB 7ab9a3c9 download
Qwen3.6-27B-abliterated-v2.i1-IQ2_XXS.gguf 7.85 GB 318d4706 download
IQ1 2 files 13.8 GB
Qwen3.6-27B-abliterated-v2.i1-IQ1_M.gguf 7.11 GB 2cdbe671 download
Qwen3.6-27B-abliterated-v2.i1-IQ1_S.gguf 6.66 GB 5ae1dd73 download
Auxiliary files 3 files 13.0 MB
Qwen3.6-27B-abliterated-v2.imatrix.gguf 13.0 MB d41b0c2e download
README.md 6.51 KB d272e20c download
.gitattributes 3.30 KB c2874f42 download

README current version from Hugging Face


base_model: wangzhang/Qwen3.6-27B-abliterated
language:

  • en
  • zh
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • abliterated
  • uncensored
  • dense
  • qwen3.6
  • hybrid-attention
  • gated-deltanet
  • vlm
  • lora-search-merged-release
  • abliterix
  • deeprefusal-peel
  • iterative-abliteration

About

weighted/imatrix quants of https://huggingface.co/wangzhang/Qwen3.6-27B-abliterated

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

static quants are available at https://huggingface.co/mradermacher/Qwen3.6-27B-abliterated-v2-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 7.2 for the desperate
GGUF i1-IQ1_M 7.7 mostly desperate
GGUF i1-IQ2_XXS 8.5
GGUF i1-IQ2_XS 9.2
GGUF i1-IQ2_S 9.5
GGUF i1-IQ2_M 10.1
GGUF i1-Q2_K_S 10.3 very low quality
GGUF i1-Q2_K 10.8 IQ3_XXS probably better
GGUF i1-IQ3_XXS 11.3 lower quality
GGUF i1-IQ3_XS 12.1
GGUF i1-Q3_K_S 12.2 IQ3_XS probably better
GGUF i1-IQ3_S 12.5 beats Q3_K*
GGUF i1-IQ3_M 12.7
GGUF i1-Q3_K_M 13.4 IQ3_S probably better
GGUF i1-Q3_K_L 14.4 IQ3_M probably better
GGUF i1-IQ4_XS 15.2
GGUF i1-Q4_0 15.6 fast, low quality
GGUF i1-Q4_K_S 15.7 optimal size/speed/quality
GGUF i1-Q4_K_M 16.6 fast, recommended
GGUF i1-Q4_1 17.2
GGUF i1-Q5_K_S 18.8
GGUF i1-Q5_K_M 19.3
GGUF i1-Q6_K 22.2 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 5 versions

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

  1. 2026-08-29auto-patch README.md07c35226.5 KB
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  2. 2026-05-08auto-patch README.mddf65c416.5 KB
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  3. 2026-05-08auto-patch README.md831bb9d5.1 KB
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  4. 2026-05-08auto-patch README.md9a5869d2.9 KB
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  5. 2026-05-08uploaded from nico17e36ff8483 B
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