license: apache-2.0 tags:

• uncensored
• qwen3.6
• moe
• gguf
• text
• tools language:
• en
• zh
• multilingual pipeline_tag: text-generation base_model: Qwen/Qwen3.6-35B-A3B

Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive

Note from braydenh563: Q4_K_M is still Q4_K_P but just renamed so that I can pull it directly into ollama. Same for the others.

Join the Discord for updates, roadmaps, projects, or just to chat.

Qwen3.6-35B-A3B uncensored by HauhauCS. 0/465 Refusals.

HuggingFace's "Hardware Compatibility" widget doesn't recognize K_P quants — it may show fewer files than actually exist. Click "View +X variants" or go to Files and versions to see all available downloads.

About

No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.

These are meant to be the best lossless uncensored models out there.

Aggressive Variant

Stronger uncensoring — model is fully unlocked and won't refuse prompts. May occasionally append short disclaimers (baked into base model training, not refusals) but full content is always generated.

For a more conservative uncensor that keeps some safety guardrails, check the Balanced variant when it's available.

Downloads

All quants generated with importance matrix (imatrix) for optimal quality preservation on abliterated weights.

What are K_P quants?

K_P ("Perfect") quants are HauhauCS custom quantizations that use model-specific analysis to selectively preserve quality where it matters most. Each model gets its own optimized quantization profile.

A K_P quant effectively bumps quality up by 1-2 quant levels at only ~5-15% larger file size than the base quant. Fully compatible with llama.cpp, LM Studio, and any GGUF-compatible runtime — no special builds needed.

Note: K_P quants may show as "?" in LM Studio's quant column. This is a display issue only — the model loads and runs fine.

Specs

• 35B total parameters, ~3B active per forward pass (MoE)
• 256 experts, 8 routed per token
• Hybrid architecture: linear attention + full softmax attention (3:1 ratio)
• 40 layers
• 262K native context
• Based on Qwen/Qwen3.6-35B-A3B

Recommended Settings

From the official Qwen authors:

Thinking mode (default):

• General: temperature=1.0, top_p=0.95, top_k=20, min_p=0, presence_penalty=1.5
• Coding/precise tasks: temperature=0.6, top_p=0.95, top_k=20, min_p=0, presence_penalty=0

Non-thinking mode:

• General: temperature=0.7, top_p=0.8, top_k=20, min_p=0, presence_penalty=1.5
• Reasoning tasks: temperature=1.0, top_p=1.0, top_k=40, min_p=0, presence_penalty=2.0

Important:

• Keep at least 128K context to preserve thinking capabilities
• Use --jinja flag with llama.cpp for proper chat template handling

Usage

Works with llama.cpp, LM Studio, Jan, koboldcpp, and other GGUF-compatible runtimes.

llama-cli -m Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-Q4_K_P.gguf \
  --jinja -c 131072 -ngl 99

Other Models

• HauhauCS on HuggingFace