ZeroxZhang/Qwen3.8-27B-Uncensored-MLX-Demo
Qwen3.8-27B-Uncensored-MLX Demo
An interactive demo page for the Qwen3.8-27B-Uncensored-MLX model — an abliterated MLX build of Qwen's 27B vision-language model for Apple Silicon.
Live Chat Demo
The embedded demo below uses the PyTorch equivalent on ZeroGPU. For native MLX inference on your Mac, see the local usage instructions.
Model Overview
Qwen3.8-27B-Uncensored-MLX is an abliterated (refusal-removed) MLX build of `Qwen/Qwen3.8-27B` — a 27B-parameter dense, hybrid-attention native vision-language model with thinking control, tool-calling and an MTP head.
Key Features
- Abliterated: Safety alignment removed for research purposes
- MLX Format: Optimized for Apple Silicon (M1/M2/M3/M4)
- Vision-Language: Native image understanding capabilities
- Multiple Quantizations: 2 / 4 / 6 / 8-bit precision options
- Long Context: 262K token context window
Available Quantizations
Local Usage
# Install mlx-vlm
pip install -U mlx-vlm
# Download the 4-bit quantization
hf download orcarouter/Qwen3.8-27B-Uncensored-MLX --include "4-bit/*" \
--local-dir ./Qwen3.8-27B-Uncensored-MLX
# Text generation
python -m mlx_vlm generate \
--model ./Qwen3.8-27B-Uncensored-MLX/4-bit \
--prompt "Explain quantum entanglement in one sentence." --max-tokens 256
# Vision (image + text)
python -m mlx_vlm generate \
--model ./Qwen3.8-27B-Uncensored-MLX/4-bit \
--image path/to/image.png \
--prompt "Describe this image." --max-tokens 256
# OpenAI-compatible server
python -m mlx_vlm server --model ./Qwen3.8-27B-Uncensored-MLX/4-bit --port 8080Links
- Model: orcarouter/Qwen3.8-27B-Uncensored-MLX
- API: OrcaRouter Model API
- Base Model: Qwen/Qwen3.8-27B
- Website: orcarouter.ai
Disclaimer
This model has had its safety alignment substantially removed via abliteration. It is released strictly for legitimate research — interpretability, AI-safety and refusal-mechanism study, red-teaming, robustness evaluation, and controlled experiments. You assume full responsibility and liability for how you use it.
