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gemma-3-27b-it-abliterated

gemma-3-27b-it-abliterated is a refusal-ablated variant of google/gemma-3-27b-it, published on Hugging Face by mlabonne. It is 27B parameters, 48GB VRAM class class and gemma licence. It is distributed across 34 repositories in Transformers, GGUF, GGUF (imatrix) and MLX formats, totalling 18.6K downloads.

Abliteration (directional ablation)27BGemma25B – 50B↓ 18,612♥ 347

Specification

Model name
gemma-3-27b-it-abliterated
Publisher
mlabonne
Parameters
27B
VRAM required
~17.2 GB at Q4_K_M, 4k context (estimated) — runs on 24 GB cards
Hardware class
25B – 50B — 48GB VRAM class
Licence
gemma
Task
Image text to text
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF, GGUF (imatrix), MLX, EXL2, FP8
First indexed
16 Mar 2025
Last updated
28 Sept 2026

Ablation technique

How gemma-3-27b-it-abliterated was modified, and what that implies.

Abliteration (directional ablation)

The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

From the publisher’s model card

“This is an uncensored version of google/gemma-3-27b-it created with a new abliteration technique. See this article to know more about abliteration.”

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download mlabonne/gemma-3-27b-it-abliterated-GGUF --local-dir ./gemma-3-27b-it-abliterated
llama-cli -m ./gemma-3-27b-it-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "mlabonne/gemma-3-27b-it-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve mlabonne/gemma-3-27b-it-abliterated --trust-remote-code

Downloads and variants (33)

Every published repository of gemma-3-27b-it-abliterated, including quantised re-releases by other authors.

RepositoryFormatDownloads
mlabonne/gemma-3-27b-it-abliterated-GGUFGGUF11.7K
mlabonne/gemma-3-27b-it-abliteratedsourceTransformers2.9K
mradermacher/gemma-3-27b-it-abliterated-i1-GGUFGGUF (imatrix)1.5K
mradermacher/gemma-3-27b-it-abliterated-GGUFGGUF584
Thaurock/Gemma-3-27b-it-abliterated-GGUFGGUF528
youkoutenhouin/gemma-3-27b-it-abliterated-GGUFGGUF239
Userb1az/gemma-3-27b-it-abliterated-GGUFGGUF129
Naphula/gemma-3-27b-it-abliterated-Q8_K_XL-GGUFGGUF107
KnutJaegersberg/gemma-3-27b-it-abliterated-Q8_0-GGUFGGUF96
NovNovikov/gemma-3-27b-it-abliterated-Q4_K_M-GGUFGGUF87
Yaovi78/gemma-3-27b-it-abliterated-GGUFGGUF82
Impulse2000/gemma-3-27b-it-abliterated-Q4_K_M-GGUFGGUF58
sistabossen/gemma-3-27b-it-abliterated-mlx-4BitMLX52
Harry989/gemma-3-27b-it-abliterated-Q4_K_M-GGUFGGUF51
cyberFreak9/gemma-3-27b-it-abliterated-Q4_K_M-GGUFGGUF50
otherwhere1/gemma-3-27b-it-abliterated-mlx-8BitMLX48
EloyOn/gemma-3-27b-it-abliterated-Q5_0-GGUFGGUF41
Lucy-in-the-Sky/gemma-3-27b-it-abliterated-Q4_K_M-GGUFGGUF40
stevej1397/gemma-3-27b-it-abliterated-mlx-4BitMLX39
Lucy-in-the-Sky/gemma-3-27b-it-abliterated-Q6_K-GGUFGGUF34
Recouper/gemma-3-27b-it-abliterated-Q6_K-GGUFGGUF33
KYUNGYONG/gemma-3-27b-it-abliterated-mlx-3BitMLX32
Omnico/gemma-3-27b-it-abliterated-mlx-3BitMLX32
prithivMLmods/gemma-3-27b-it-abliterated-FP8FP827
jimjam006/gemma-3-27b-it-abliterated-Q8_0-GGUFGGUF17
danielmnd/gemma-3-27b-it-abliterated-GGUFGGUF17
QrCode99/gemma-3-27b-it-abliterated-Q8_0-GGUFGGUF16
otherhalf-dev/gemma-3-27b-it-abliterated-FP8FP810
Yaovi78/gemma-3-27b-it-abliteratedTransformers7
Ares133/gemma-3-27b-it-abliteratedTransformers6
Plus 3 further repositories with fewer downloads, all counted in the totals above.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • gemma-3-27b-it-abliterated will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • Capability is inherited from google/gemma-3-27b-it, not added by ablation — at 27B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • Declared licence is gemma, but the terms that bind you are google/gemma-3-27b-it’s — a re-release cannot grant more than its parent.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for gemma-3-27b-it-abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with mlabonne, and does not independently verify publisher claims. See responsible use.