Instructions to use audiohacking/Qwen3.8-3.6-27B-Splash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use audiohacking/Qwen3.8-3.6-27B-Splash 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("audiohacking/Qwen3.8-3.6-27B-Splash") config = load_config("audiohacking/Qwen3.8-3.6-27B-Splash") # 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 Settings
- LM Studio
- Atomic Chat
Qwen3.8-3.6-27B-Splash
Splash 1.0 schema-3 package of the JetBrains Qwen3.8 × Qwen3.6 27B blend.
splash serve --model audiohacking/Qwen3.8-3.6-27B-Splash
What is packed
| Section | Source |
|---|---|
target/ |
Packed from JetBrains/Qwen3.8-3.6-27B-blend-MLX-4bit (affine 4-bit, group 64) |
vision/ |
Packed from the same blend vision tower |
tokenizer/ |
Blend tokenizer + Splash chat-template tweak (later system messages rendered in place) |
draft/ |
Packed DFlash2 copied from incoai/Qwen3.8-27B-Splash. Splash requires this layout; drafted tokens are verified by the blend target |
This is a Hugging Face model repo. Splash will not load the BF16 bucket audiohacking/Qwen3.8-3.6-27B-blend.
JetBrains Qwen3.8-3.6-27B-blend-MTP-MLX-4bit is an mlx-vlm drafter, not a Splash draft/ replacement.
Model tree for audiohacking/Qwen3.8-3.6-27B-Splash
Base model
JetBrains/Qwen3.8-3.6-27B-blend Quantized
JetBrains/Qwen3.8-3.6-27B-blend-MLX-4bit