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unsloth
/
Qwen3.6-27B-UD-MLX-3bit

Image-Text-to-Text
MLX
Safetensors
qwen3_5
unsloth
qwen
conversational
3-bit
Model card Files Files and versions
xet
Community
1

Instructions to use unsloth/Qwen3.6-27B-UD-MLX-3bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use unsloth/Qwen3.6-27B-UD-MLX-3bit 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("unsloth/Qwen3.6-27B-UD-MLX-3bit")
    config = load_config("unsloth/Qwen3.6-27B-UD-MLX-3bit")
    
    # 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
  • LM Studio
  • Unsloth Studio new

    How to use unsloth/Qwen3.6-27B-UD-MLX-3bit 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-UD-MLX-3bit 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-UD-MLX-3bit 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-UD-MLX-3bit to start chatting
    Load model with FastModel
    pip install unsloth
    from unsloth import FastModel
    model, tokenizer = FastModel.from_pretrained(
        model_name="unsloth/Qwen3.6-27B-UD-MLX-3bit",
        max_seq_length=2048,
    )
  • Pi new

    How to use unsloth/Qwen3.6-27B-UD-MLX-3bit with Pi:

    Start the MLX server
    # Install MLX LM:
    uv tool install mlx-lm
    # Start a local OpenAI-compatible server:
    mlx_lm.server --model "unsloth/Qwen3.6-27B-UD-MLX-3bit"
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "mlx-lm": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "unsloth/Qwen3.6-27B-UD-MLX-3bit"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
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Quick question: I noticed your MLX 3-bit variant sits at ~24GB, while GGUF’s Q3_K_S is only ~12.4GB?

👀 1
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#1 opened 14 days ago by
realperson1234
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