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---
language:
- en
- zh
library_name: mlx
license: mit
pipeline_tag: text-generation
base_model: zai-org/GLM-4.6
tags:
- mlx
---
**See GLM-4.6 6.5bit MLX in action - [demonstration video](https://youtu.be/bOfoCocOjfM)**
*q6.5bit quant typically achieves the highest perplexity in our testing*
| Quantization | Perplexity |
|:------------:|:----------:|
| **q2.5** | 41.293 |
| **q3.5** | 1.900 |
| **q4.5** | 1.168 |
| **q5.5** | 1.141 |
| **q6.5** | 1.128 |
| **q8.5** | 1.128 |
## Usage Notes
* Runs on a single M3 Ultra 512GB RAM using [Inferencer app](https://inferencer.com)
* Memory usage: ~270 GB
* Expect ~16 tokens/s
* Quantized with a modified version of [MLX](https://github.com/ml-explore/mlx) 0.27
* For more details see [demonstration video](https://youtu.be/bOfoCocOjfM) or visit [GLM-4.6](https://huggingface.co/zai-org/GLM-4.6).
## Disclaimer
We are not the creator, originator, or owner of any model listed. Each model is created and provided by third parties. Models may not always be accurate or contextually appropriate. You are responsible for verifying the information before making important decisions. We are not liable for any damages, losses, or issues arising from its use, including data loss or inaccuracies in AI-generated content. |