Instructions to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport",
	filename="hauhau_qwen36_35b_a3b_mxfp4_mtp.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": [
				{
					"type": "text",
					"text": "Describe this image in one sentence."
				},
				{
					"type": "image_url",
					"image_url": {
						"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
# Run inference directly in the terminal:
llama cli -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
# Run inference directly in the terminal:
llama cli -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Use Docker

docker model run hf.co/robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

LM Studio
Jan

vLLM

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Ollama
How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Ollama:
```
ollama run hf.co/robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
```

Unsloth Studio

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport to start chatting

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

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 robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

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 "robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

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

Docker Model Runner
How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Docker Model Runner:
```
docker model run hf.co/robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0
```

Lemonade

How to use robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport:Q8_0

Run and chat with the model

lemonade run user.hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport-Q8_0

List all available models

lemonade list

hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport

This repo contains the local serving package for HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive using a robinshao-style MXFP4_MOE main GGUF, a separate MTP draft GGUF for speculative decoding, and a separate multimodal mmproj GGUF for image input support in patched llama.cpp.

Files

hauhau_qwen36_35b_a3b_mxfp4_robinstyle.gguf: main text model in robinshao-style MXFP4 layout
hauhau_qwen36_35b_a3b_mxfp4_mtp.gguf: MTP draft GGUF used with --spec-type draft-mtp
mmproj-Hauhau_Qwen36_35B_A3B_Fp16-Q8_0.gguf: multimodal projector / vision encoder GGUF
llama.cpp.src-patched.zip: patched local llama.cpp source snapshot used for conversion and serving
build_result.json: build and validation summary
mtp-benchmark.json: short local speed comparison for the text+MTP serving pair

Package Notes

Source FP16 weights: khoi11/Qwen3.6-35B-A3B-Uncensored-HauhauCS-FP16
Upstream model lineage: HauhauCS/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive
Main model and draft model reuse the previously validated robinshao-style MXFP4 + MTP export
Visual support is provided by a newly exported mmproj GGUF from the original multimodal FP16 checkpoint
This serving package is multimodal only when the main model is loaded together with the mmproj file

Local Deployment Notes

Validated locally on Windows with patched llama.cpp using speculative decoding and multimodal input:

llama-server -m hauhau_qwen36_35b_a3b_mxfp4_robinstyle.gguf   --mmproj mmproj-Hauhau_Qwen36_35B_A3B_Fp16-Q8_0.gguf   --spec-type draft-mtp   --spec-draft-model hauhau_qwen36_35b_a3b_mxfp4_mtp.gguf   --spec-draft-device CUDA0   --spec-draft-ngl all   --jinja   --device CUDA0   --gpu-layers all   --ctx-size 8192   --batch-size 512   --ubatch-size 128   --flash-attn on   --cache-type-k f16   --cache-type-v f16   --cache-ram 0

Local validation confirmed:

the model still loads with draft-mtp
the mmproj loads successfully
/v1/chat/completions accepts image input
a real image smoke test identified the primary object correctly

Caveats

The main GGUF and MTP draft are still the same text-focused MXFP4 exports; visual support comes from the additional mmproj file.
If you omit --mmproj, the package behaves like the earlier text-only MTP release.
Native training context metadata remains 262144, but local no-offload limits still depend on VRAM, KV cache settings, and whether the draft model is loaded.

Downloads last month: 316

GGUF

Model size

35B params

Architecture

qwen35moe

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Model tree for robinshao/hauhau_qwen36_35b_a3b_mxfp4_gguf_mtp_visualsupport

Base model

Qwen/Qwen3.6-35B-A3B

Quantized

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

Quantized

(20)

this model