Instructions to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ",
	filename="MoQ-Quants/MoQ-3.3.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ 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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
# Run inference directly in the terminal:
llama cli -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
# Run inference directly in the terminal:
llama cli -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
# Run inference directly in the terminal:
./llama-cli -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
# Run inference directly in the terminal:
./build/bin/llama-cli -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

Use Docker

docker model run hf.co/w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

LM Studio
Jan

vLLM

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

Ollama
How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with Ollama:
```
ollama run hf.co/w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
```

Unsloth Studio

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ 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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ 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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ to start chatting

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

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": "w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

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 "w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ" \
  --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 w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with Docker Model Runner:
```
docker model run hf.co/w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ
```

Lemonade

How to use w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull w-ahmad/Qwopus3.5-9B-Coder-MTP-GGUF-MoQ

Run and chat with the model

lemonade run user.Qwopus3.5-9B-Coder-MTP-GGUF-MoQ-{{QUANT_TAG}}

List all available models

lemonade list

Qwopus3.5-9B-Coder no MTP request

by TalasCloud - opened Jun 10

Discussion

TalasCloud

Jun 10

Hi. Can you please make a Qwopus3.5-9B-Coder - no mtp gguf variant? I have only 8gb vram, experimenting to push qwen coder to it's limits maintaining the 64kcontext on low vram and comparing speeds. For some reason MTP is making slower on my HW (like double slower)..So, if it's possible MOE and no MTP please 😀 Thanks in advance!

https://huggingface.co/Jackrong/Qwopus3.5-9B-Coder or https://huggingface.co/armand0e/Qwen3.5-9B-Coder
which one is better for coding in agentic mode...

p.s. can you please tell the difference btw MoE and weighted/imatrix ? - like this one - https://huggingface.co/mradermacher/Qwen3.5-9B-Coder-i1-GGUF

thank you very much.

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