Instructions to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with MLX:

# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm

from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config

# Load the model
model, processor = load("TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8")
config = load_config("TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8")

# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."

# Apply chat template
formatted_prompt = apply_chat_template(
    processor, config, prompt, num_images=1
)

# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "TheCluster/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive-MLX-mxfp8 / README.md

TheCluster

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metadata

license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3.5-27B/blob/main/LICENSE
base_model:
  - HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive
base_model_relation: quantized
library_name: mlx
tags:
  - uncensored
  - unrestricted
  - decensored
  - mxfp8
pipeline_tag: image-text-to-text
language:
  - en
  - zh
  - ru
  - es
  - fr
  - it
  - ja
  - ko
  - af
  - de
  - ar
  - tr
  - is
  - pl
  - sw
  - sv
  - nl
  - he
  - id
  - uk
  - fa
  - pa
  - pt
  - ms
  - fi
  - el

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

Qwen3.5-35B-A3B uncensored by HauhauCS.

Quality: quantized (mxfp8, group size: 32, 8.349 bpw)

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 with more thorough refusal removal. If this variant is too loose for your use case, a Balanced variant may follow.

Note: The model is fully unlocked and will not refuse prompts. However, it may occasionally append a short disclaimer at the end of a response (e.g. "This is general information, not legal advice..."). This is baked into the base model's training and not a refusal — the actual content is still generated in full.

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

Source

This model was converted to MLX format from HauhauCS/Qwen3.5-35B-A3B-Uncensored-HauhauCS-Aggressive