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Kataguru-Sceptic-35B-A3B-v2.6

Kataguru-Sceptic-35B-A3B-v2.6 is a abliterated and uncensored variant of Qwen/Qwen3.5-35B-A3B, published on Hugging Face by kataguru. It is 35B total parameters (mixture-of-experts), 48GB VRAM class class and apache-2.0 licence. It is distributed across 4 repositories in GGUF, AWQ and NVFP4 formats, totalling 6.4K downloads.

Abliteration + uncensored fine-tune35B MoEOther25B – 50B↓ 6,431

Specification

Model name
Kataguru-Sceptic-35B-A3B-v2.6
Publisher
kataguru
Parameters
35B (mixture-of-experts)
VRAM required
~22.1 GB at Q4_K_M, 4k context (estimated) — runs on 24 GB cards
Hardware class
25B – 50B — 48GB VRAM class
Licence
apache-2.0
Task
Image text to text
Context window
32K tokens (as documented)
Ablation scope
Not stated by the publisher
Formats available
GGUF, AWQ, NVFP4
First indexed
15 Oct 2026
Last updated
28 Oct 2026

Ablation technique

How Kataguru-Sceptic-35B-A3B-v2.6 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

“Kataguru-Sceptic-35B-A3B-v2.6-GGUF is the llama.cpp / LM Studio / Ollama GGUF release of Kataguru-Sceptic-35B-A3B-v2.6, a bilingual (English & Finnish) 35-billion parameter (3B active parameters per token, 254 routed experts per layer) multimodal Mixture-of-Experts (MoE) model.”

Running it

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

llama.cpp / GGUF
hf download kataguru/Kataguru-Sceptic-35B-A3B-v2.6-GGUF --local-dir ./kataguru-sceptic-35b-a3b-v2.6
llama-cli -m ./kataguru-sceptic-35b-a3b-v2.6/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "kataguru/Kataguru-Sceptic-35B-A3B-v2.6-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve kataguru/Kataguru-Sceptic-35B-A3B-v2.6-GGUF --trust-remote-code

Downloads and variants (3)

Every published repository of Kataguru-Sceptic-35B-A3B-v2.6, 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.

  • Kataguru-Sceptic-35B-A3B-v2.6 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 Qwen/Qwen3.5-35B-A3B, not added by ablation — at 35B 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 apache-2.0, but the terms that bind you are Qwen/Qwen3.5-35B-A3B’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 Kataguru-Sceptic-35B-A3B-v2.6 is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with kataguru, and does not independently verify publisher claims. See responsible use.