Instructions to use ggml-org/Qwen3.6-27B-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ggml-org/Qwen3.6-27B-MTP-GGUF", filename="Qwen3.6-27B-MTP-BF16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
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 ggml-org/Qwen3.6-27B-MTP-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
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 ggml-org/Qwen3.6-27B-MTP-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
Use Docker
docker model run hf.co/ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
- LM Studio
- Jan
- Ollama
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with Ollama:
ollama run hf.co/ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
- Unsloth Studio new
How to use ggml-org/Qwen3.6-27B-MTP-GGUF 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 ggml-org/Qwen3.6-27B-MTP-GGUF 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 ggml-org/Qwen3.6-27B-MTP-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ggml-org/Qwen3.6-27B-MTP-GGUF to start chatting
- Pi new
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
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": "ggml-org/Qwen3.6-27B-MTP-GGUF:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
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 ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
Run Hermes
hermes
- Docker Model Runner
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with Docker Model Runner:
docker model run hf.co/ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
- Lemonade
How to use ggml-org/Qwen3.6-27B-MTP-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ggml-org/Qwen3.6-27B-MTP-GGUF:BF16
Run and chat with the model
lemonade run user.Qwen3.6-27B-MTP-GGUF-BF16
List all available models
lemonade list
How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16# Run inference directly in the terminal:
llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16Use 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 ggml-org/Qwen3.6-27B-MTP-GGUF:BF16# Run inference directly in the terminal:
./llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16Build 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 ggml-org/Qwen3.6-27B-MTP-GGUF:BF16# Run inference directly in the terminal:
./build/bin/llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16Use Docker
docker model run hf.co/ggml-org/Qwen3.6-27B-MTP-GGUF:BF16Quick Links
Qwen3.6-27B-MTP GGUF
Recommended way to run this model:
# max MTP draft of 2 tokens
llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF --spec-type draft-mtp --spec-draft-n-max 2
# max MTP draft of 3 tokens
llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF --spec-type draft-mtp --spec-draft-n-max 3
Then, access http://localhost:8080
Requires the changes from: https://github.com/ggml-org/llama.cpp/pull/22673
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Base model
Qwen/Qwen3.6-27B
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16# Run inference directly in the terminal: llama-cli -hf ggml-org/Qwen3.6-27B-MTP-GGUF:BF16