README.md

---
language:
- en
- zh
license: other
license_name: glm-4-license
pipeline_tag: text-generation
tags:
- mlx
- glm4
- moe
- prism
- abliterated
- 4bit
- quantized
- apple-silicon
library_name: mlx
base_model: Ex0bit/GLM-4.7-Flash-PRISM
---

<p align="center">
  <a href="https://vmlx.net">
    <img src="vmlx-logo.png" alt="vMLX" width="120">
  </a>
</p>

# GLM-4.7-Flash-PRISM — MLX 4-bit

MLX 4-bit quantized version of [Ex0bit/GLM-4.7-Flash-PRISM](https://huggingface.co/Ex0bit/GLM-4.7-Flash-PRISM) for efficient local inference on Apple Silicon.

- **Quantization**: 4-bit (4.5 bits per weight, group size 64, affine mode)
- **Architecture**: GLM-4 MoE Lite — 47 layers, 64 routed experts, 4 active per token
- **Context**: 202K tokens
- **Size**: ~16 GB

## Usage

```python
from mlx_lm import load, generate

model, tokenizer = load("shieldstackllc/GLM-4.7-Flash-PRISM-mlx-4bit")
response = generate(model, tokenizer, prompt="Hello!", verbose=True)
```

Or with [vMLX](https://vmlx.net) for native macOS inference.

## About

This model is an abliterated (uncensored) variant of GLM-4.7-Flash, a Mixture-of-Experts language model by Zhipu AI / THUDM. The abliteration was done by [Ex0bit](https://huggingface.co/Ex0bit) as part of the PRISM series. MLX quantization by [vMLX](https://vmlx.net).

## Also Available

- [GLM-4.7-Flash-PRISM MLX 8-bit](https://huggingface.co/shieldstackllc/GLM-4.7-Flash-PRISM-mlx-8bit) (~30 GB)

## Made for vMLX

This model was converted and optimized for [vMLX](https://vmlx.net) — a free, open source macOS native MLX inference engine for Apple Silicon. Download vMLX to run this model locally with zero configuration.

## Credits

- **Base model**: [THUDM/GLM-4](https://github.com/THUDM/GLM-4) by Zhipu AI
- **Abliteration**: [Ex0bit/GLM-4.7-Flash-PRISM](https://huggingface.co/Ex0bit/GLM-4.7-Flash-PRISM)
- **MLX conversion**: [vMLX](https://vmlx.net) — Run AI locally on Mac. No compromises.

## Contact

For questions, issues, or collaboration: **admin@vmlx.net**