abliteratedmodels.org

gemma-4-31B-it-abliterated

gemma-4-31B-it-abliterated is a refusal-ablated variant of google/gemma-4-31B-it, published on Hugging Face by wangzhang. It is 31B parameters, 48GB VRAM class class and apache-2.0 licence. It is distributed across 46 repositories in Transformers, GGUF (imatrix), GGUF and MLX formats, totalling 766.5K downloads.

Abliteration (directional ablation)31BGemma25B – 50B766,546118

Specification

Model name
gemma-4-31B-it-abliterated
Publisher
wangzhang
Parameters
31B
Hardware class
25B – 50B — 48GB VRAM class
Licence
apache-2.0
Task
Unspecified
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF (imatrix), GGUF, MLX, NVFP4, FP8
First indexed
2 Apr 2026
Last updated
30 Aug 2026

Ablation technique

How gemma-4-31B-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 abliterated version of google/gemma-4-31B-it, created using Abliterix.

Running it

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

llama.cpp / GGUF
hf download paperscarecrow/Gemma-4-31B-it-abliterated --local-dir ./gemma-4-31b-it-abliterated
llama-cli -m ./gemma-4-31b-it-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "wangzhang/gemma-4-31B-it-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve wangzhang/gemma-4-31B-it-abliterated --trust-remote-code

Downloads and variants (45)

Every published repository of gemma-4-31B-it-abliterated, including quantised re-releases by other authors.

RepositoryFormatDownloads
wangzhang/gemma-4-31B-it-abliteratedsourceTransformers601.6K
paperscarecrow/Gemma-4-31B-it-abliteratedGGUF135.1K
huihui-ai/Huihui-gemma-4-31B-it-abliteratedTransformers8.2K
mradermacher/gemma-4-31B-it-abliterated-i1-GGUFGGUF (imatrix)6.7K
wangzhang/gemma-4-31B-it-abliterated-GGUFGGUF3.9K
mradermacher/gemma-4-31B-it-abliterated-GGUFGGUF2.3K
LiconStudio/Gemma-4-31B-it-abliterated-GGUFGGUF2.1K
mradermacher/Huihui-gemma-4-31B-it-abliterated-GGUFGGUF1.3K
mradermacher/Huihui-gemma-4-31B-it-abliterated-i1-GGUFGGUF (imatrix)828
divinetribe/gemma-4-31b-it-abliterated-4bit-mlxMLX818
aday777/gemma-4-31B-it-abliterated-NVFP4NVFP4510
divinetribe/Huihui-gemma-4-31B-it-abliterated-4bit-mlxMLX406
cs2764/gemma-4-31b-it-8bit-abliterated-mlxMLX405
dryade36513/Gemma-4-31B-it-abliterated-GGUFGGUF405
lhca521/gemma-4-31B-it-abliterated-i1-GGUFGGUF (imatrix)278
amarck/gemma-4-31b-it-abliterated-GGUFGGUF273
McG-221/gemma-4-31B-it-abliterated-8bitMLX231
zenlogic/Huihui-gemma-4-31B-it-abliterated-mlx-8BitMLX148
zenlogic/Huihui-gemma-4-31B-it-abliterated-mlx-fp16MLX141
cs2764/gemma-4-31b-it-6bit-abliterated-mlxMLX131
zenlogic/Huihui-gemma-4-31B-it-abliterated-mlx-6BitMLX107
nguyenthilaitrieulong/gemma-4-31B-it-abliteratedTransformers103
zenlogic/Huihui-gemma-4-31B-it-abliterated-mlx-4BitMLX84
stronman/Gemma-4-31B-it-abliterated-GGUFGGUF79
null-space/gemma-4-31b-it-abliteratedTransformers78
lhca521/gemma-4-31B-it-abliterated-GGUFGGUF74
WWTCyberLab/gemma-4-31B-it-abliteratedTransformers69
0xA50C1A1/gemma-4-31B-it-abliterated-ggufGGUF68
JustinChung1111/Gemma-4-31B-it-abliteratedGGUF65
hlililililili/Gemma-4-31B-it-abliteratedGGUF35
Plus 15 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-4-31B-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-4-31B-it, not added by ablation — at 31B 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 apache-2.0, but the terms that bind you are google/gemma-4-31B-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-4-31B-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 wangzhang, and does not independently verify publisher claims. See responsible use.