Qwen3.8-27B-abliterated
27BQwen
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Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated
Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated is a refusal-ablated variant of lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled, published on Hugging Face by huihui-ai. It is 35B total parameters (mixture-of-experts), 48GB VRAM class class and apache-2.0 licence. It is distributed across 45 repositories in GGUF, MLX, GGUF (imatrix) and Transformers formats, totalling 74.8K downloads.
Specification
- Model name
- Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated
- Source repository
- huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated
- Publisher
- huihui-ai
- 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
- Text generation
- Context window
- Not documented
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF, MLX, GGUF (imatrix), Transformers, FP8, NVFP4, EXL3
- First indexed
- 21 Apr 2026
- Last updated
- 1 Nov 2026
Ablation technique
How Qwen3.6-35B-A3B-Claude-4.7-Opus-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 lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
Ollama (publisher-documented)
ollama run huihui_ai/Qwen3.6-abliterated:35b-Claude-4.7llama.cpp / GGUF
hf download huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-MTP-GGUF --local-dir ./qwen3.6-35b-a3b-claude-4.7-opus-abliterated
llama-cli -m ./qwen3.6-35b-a3b-claude-4.7-opus-abliterated/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve huihui-ai/Huihui-Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated --trust-remote-codeDownloads and variants (44)
Every published repository of Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated, 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.
- Qwen3.6-35B-A3B-Claude-4.7-Opus-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 lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled, 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.
- Declared licence is apache-2.0, but the terms that bind you are lordx64/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled’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 Qwen3.6-35B-A3B-Claude-4.7-Opus-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 huihui-ai, and does not independently verify publisher claims. See responsible use.