Instructions to use unsloth/Qwen3.6-27B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/Qwen3.6-27B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="unsloth/Qwen3.6-27B-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/Qwen3.6-27B-GGUF", dtype="auto") - llama-cpp-python
How to use unsloth/Qwen3.6-27B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unsloth/Qwen3.6-27B-GGUF", filename="BF16/Qwen3.6-27B-BF16-00001-of-00002.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 unsloth/Qwen3.6-27B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
- LM Studio
- Jan
- vLLM
How to use unsloth/Qwen3.6-27B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "unsloth/Qwen3.6-27B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unsloth/Qwen3.6-27B-GGUF", "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/unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
- SGLang
How to use unsloth/Qwen3.6-27B-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "unsloth/Qwen3.6-27B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unsloth/Qwen3.6-27B-GGUF", "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 images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "unsloth/Qwen3.6-27B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "unsloth/Qwen3.6-27B-GGUF", "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" } } ] } ] }' - Ollama
How to use unsloth/Qwen3.6-27B-GGUF with Ollama:
ollama run hf.co/unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
- Unsloth Studio
How to use unsloth/Qwen3.6-27B-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 unsloth/Qwen3.6-27B-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 unsloth/Qwen3.6-27B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/Qwen3.6-27B-GGUF to start chatting
- Pi
How to use unsloth/Qwen3.6-27B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
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": "unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use unsloth/Qwen3.6-27B-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 unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
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 unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Docker Model Runner
How to use unsloth/Qwen3.6-27B-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Qwen3.6-27B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Qwen3.6-27B-GGUF-UD-Q4_K_XL
List all available models
lemonade list
Update README.md
Browse files
README.md
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---
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tags:
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- unsloth
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base_model:
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library_name: transformers
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license: apache-2.0
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license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE
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pipeline_tag: image-text-to-text
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---
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# Qwen3.6-27B
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year = {2026},
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url = {https://qwen.ai/blog?id=qwen3.6-27b}
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}
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```
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---
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library_name: transformers
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license: apache-2.0
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license_link: https://huggingface.co/Qwen/Qwen3.6-27B/blob/main/LICENSE
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pipeline_tag: image-text-to-text
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base_model:
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- Qwen/Qwen3.6-27B
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tags:
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- unsloth
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- qwen
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---
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# Read our How to [Run Qwen3.6 Guide!](https://unsloth.ai/docs/models/qwen3.6)
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<div>
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<p style="margin: 0 0 0px 0; margin-top: 0px;">
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<em>See <a href="https://unsloth.ai/docs/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0 GGUFs</a> for our quantization benchmarks.</em>
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</p>
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<div style="display: flex; gap: 5px; align-items: center; margin-bottom: 0px;">
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<a href="https://github.com/unslothai/unsloth/">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133">
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</a>
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<a href="https://discord.gg/unsloth">
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<img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173">
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</a>
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<a href="https://unsloth.ai/docs/models/qwen3.6">
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143">
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</a>
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</div>
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<ul style="margin: 0;">
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<li>Developer Role Support so Qwen3.6 can work in Codex, OpenCode and more!</li>
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<li>Qwen3.6 can now be run and fine-tuned in <a href="https://unsloth.ai/docs/new/studio">Unsloth Studio</a>. <a href="https://unsloth.ai/docs/models/qwen3.6">Read our guide</a>.</li>
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<li>Tool calling improvements: Makes parsing nested objects to make tool calling succeed more.</li>
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<li>Example of Qwen3.6-35B-A3B (2-bit GGUF) running in Unsloth Studio with tool-calling:</li>
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</ul>
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</div>
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<img width="600" alt="qwen3.6 in unsloth studio" src="https://cdn-uploads.huggingface.co/production/uploads/62ecdc18b72a69615d6bd857/wRyC_xcMidEnz4INKA1b-.gif" />
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---
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# Qwen3.6-27B
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year = {2026},
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url = {https://qwen.ai/blog?id=qwen3.6-27b}
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}
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```
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