Gemma4-26B-A4B-QAT-Uncensored-HauhauCS-Balanced
26BGemmauncensored
from google/gemma-4-26B-A4B-it
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supergemma4-26b-uncensored-v2
supergemma4-26b-uncensored-v2 is a abliterated and uncensored variant of google/gemma-4-26B-A4B-it, published on Hugging Face by Jiunsong. It is 26B parameters, 48GB VRAM class class and gemma licence. It is distributed across 43 repositories in GGUF and MLX formats, totalling 394K downloads.
Specification
- Model name
- supergemma4-26b-uncensored-v2
- Source repository
- Jiunsong/supergemma4-26b-uncensored-gguf-v2
- Base model
- google/gemma-4-26B-A4B-it
- Publisher
- Jiunsong
- Parameters
- 26B
- Hardware class
- 25B – 50B — 48GB VRAM class
- Licence
- gemma
- Task
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, MLX
- First indexed
- 10 Apr 2026
- Last updated
- 12 Jul 2026
Ablation technique
How supergemma4-26b-uncensored-v2 was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
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 release is for people who want three things together:”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download Jiunsong/supergemma4-26b-uncensored-gguf-v2 --local-dir ./supergemma4-26b-uncensored-v2
llama-cli -m ./supergemma4-26b-uncensored-v2/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "Jiunsong/supergemma4-26b-uncensored-gguf-v2"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve Jiunsong/supergemma4-26b-uncensored-gguf-v2 --trust-remote-codeDownloads and variants (42)
Every published repository of supergemma4-26b-uncensored-v2, including quantised re-releases by other authors.
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- supergemma4-26b-uncensored-v2 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-4-26B-A4B-it, not added by ablation — at 26B 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.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
- Declared licence is gemma, but the terms that bind you are google/gemma-4-26B-A4B-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 supergemma4-26b-uncensored-v2 is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with Jiunsong, and does not independently verify publisher claims. See responsible use.