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mradermacher/Qwen3.8-27B-ABLITERATED-BF16-GGUF

mradermacher Qwen 27B GGUF multimodal second-order 262K ctx
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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/mradermacher%2FQwen3.8-27B-ABLITERATED-BF16-GGUF"
Response includes
  • classification m8
  • files 15
  • hub_downloads_all_time 3,451
  • 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='Blackfrost-AI/Qwen3.8-27B-ABLITERATED-BF16' (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
3K
972 last 30d - stable
Likes
0
Model age
8w ago
created 2026-08-15
Downloads over time
Now3.8K→from2.2K↑74%
2.1K2.7K3.3K3.9K2.2K on Aug 193.8K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 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
apache-2.0
Languages
en
Quantizations
BF16
Tags
transformers gguf qwen3.8 qwen 27b bf16 dense vision-language derisked research security-research red-teaming

Related

Total size
176 GB
Files
15
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2026-08-15 21:41

Files by quantization

BF16 13 files 178 GB
Qwen3.8-27B-ABLITERATED-BF16.Q8_0.gguf 27.1 GB 0c953008 download
Qwen3.8-27B-ABLITERATED-BF16.Q6_K.gguf 20.9 GB 5c75c136 download
Qwen3.8-27B-ABLITERATED-BF16.Q5_K_M.gguf 18.2 GB 0b5a52dc download
Qwen3.8-27B-ABLITERATED-BF16.Q5_K_S.gguf 17.7 GB 7274ded1 download
Qwen3.8-27B-ABLITERATED-BF16.Q4_K_M.gguf 15.7 GB 79a766e8 download
Qwen3.8-27B-ABLITERATED-BF16.Q4_K_S.gguf 14.7 GB b4bae6c2 download
Qwen3.8-27B-ABLITERATED-BF16.IQ4_XS.gguf 14.4 GB 5831fc5e download
Qwen3.8-27B-ABLITERATED-BF16.Q3_K_L.gguf 13.6 GB 79b3793b download
Qwen3.8-27B-ABLITERATED-BF16.Q3_K_M.gguf 12.6 GB ff3a6ad6 download
Qwen3.8-27B-ABLITERATED-BF16.Q3_K_S.gguf 11.4 GB 554dd2d8 download
Qwen3.8-27B-ABLITERATED-BF16.Q2_K.gguf 10.1 GB 7798d479 download
Qwen3.8-27B-ABLITERATED-BF16.mmproj-f16.gguf 885 MB 345028e6 download
Qwen3.8-27B-ABLITERATED-BF16.mmproj-Q8_0.gguf 600 MB 883d1e6a download
Auxiliary files 2 files 6.63 KB
README.md 4.17 KB 282309e0 download
.gitattributes 2.46 KB b8a221dc download

README current version from Hugging Face


base_model: Blackfrost-AI/Qwen3.8-27B-ABLITERATED-BF16
language:

  • en
    library_name: transformers
    license: apache-2.0
    mradermacher:
    readme_rev: 1
    quantized_by: mradermacher
    tags:
  • qwen3.8
  • qwen
  • 27b
  • bf16
  • dense
  • vision-language
  • derisked
  • research
  • security-research
  • red-teaming
  • coding
  • tool-calling
  • long-context
  • public-research-preview

About

static quants of https://huggingface.co/Blackfrost-AI/Qwen3.8-27B-ABLITERATED-BF16

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3.8-27B-ABLITERATED-BF16-i1-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 mmproj-Q8_0 0.7 multi-modal supplement
GGUF mmproj-f16 1.0 multi-modal supplement
GGUF Q2_K 11.0
GGUF Q3_K_S 12.4
GGUF Q3_K_M 13.6 lower quality
GGUF Q3_K_L 14.7
GGUF IQ4_XS 15.5
GGUF Q4_K_S 15.9 fast, recommended
GGUF Q4_K_M 16.9 fast, recommended
GGUF Q5_K_S 19.1
GGUF Q5_K_M 19.6
GGUF Q6_K 22.5 very good quality
GGUF Q8_0 29.1 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 5 versions

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

  1. 2026-08-15auto-patch README.mdecc8ae64.2 KB
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  2. 2026-08-15auto-patch README.mdbac4bf84.3 KB
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  3. 2026-08-15auto-patch README.mdb588d244 KB
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  4. 2026-08-15auto-patch README.md429a5283.5 KB
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  5. 2026-08-15uploaded from rich1da137b2385 B
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