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

File	Quant	Size
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-BF16.gguf	BF16	65 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q8_0.gguf	Q8_0	35 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q6_K.gguf	Q6_K	27 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q5_K_M.gguf	Q5_K_M	24 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf	Q4_K_M	20 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ4_XS.gguf	IQ4_XS	18 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q3_K_M.gguf	Q3_K_M	16 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ3_M.gguf	IQ3_M	15 GB
Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ2_M.gguf	IQ2_M	11 GB
mmproj-Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-f16.gguf	mmproj (f16)	858 MB

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

Specs

35B total parameters, ~3B active per forward pass (MoE)
256 experts, 8 routed + 1 shared per token
Hybrid architecture: Gated DeltaNet linear attention + full softmax attention (3:1 ratio)
40 layers, pattern: 10 x (3 x DeltaNet-MoE + 1 x Attention-MoE)
262K native context (extendable to 1M with YaRN)
Natively multimodal (text, image, video)
Multi-token prediction (MTP) support
248K vocabulary, 201 languages
Based on Qwen/Qwen3.5-35B-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
Vision support requires the mmproj file alongside the main GGUF

Usage

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

bash

# Text only
llama-cli -m Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf \
  --jinja -c 131072 -ngl 99

# With vision
llama-cli -m Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-Q4_K_M.gguf \
  --mmproj mmproj-Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-f16.gguf \
  --jinja -c 131072 -ngl 99

Note: LM Studio may show 256x2.6B in the params column instead of 35B-A3B — this is a cosmetic metadata quirk, the model runs correctly.

Other Formats

GGUF (this repo)
GPTQ — coming soon

Other Models

Qwen3.5-27B-Uncensored-HauhauCS-Aggressive

VECTORVV1/Qwen3-Coder-30B-A3B-Instruct

Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive

About

Aggressive Variant