---
base_model: Qwen/Qwen3-1.7B
pipeline_tag: text-generation
tags:
- qwen3
- edgerazor
- quantization
license: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen3-1.7B/blob/main/LICENSE
---

<div align="center">
  <br/>
  <img src="./asset/Logo-HF.png" alt="EdgeRazor Logo" width="60%">
  <h3>
    EdgeRazor for Lightweight LLMs
  </h3>

  <p>
    <a href="https://arxiv.org/abs/2605.04062" target="blank">
      <img src="https://img.shields.io/badge/arXiv-EdgeRazor-b31b1b?style=flat&logo=arxiv" alt="arXiv EdgeRazor">
    </a>
    <a href="https://github.com/zhangsq-nju/EdgeRazor" target="blank">
      <img src="https://img.shields.io/badge/GitHub-EdgeRazor-blue?style=flat&logo=github" alt="GitHub EdgeRazor">
    </a>
    <a href="https://pypi.org/project/edgerazor/" target="blank">
      <img src="https://img.shields.io/pypi/v/edgerazor?style=flat&logo=pypi" alt="PyPI EdgeRazor">
    </a>
  </p>


</div>

## Contents

- [Contents](#contents)
- [Model Overview](#model-overview)
- [Model Bit-Widths](#model-bit-widths)
- [Get Started](#get-started)
- [Citation](#citation)

## Model Overview

- Base Model: [Qwen/Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B)
- Training: [zhangsq-nju/EdgeRazor](https://github.com/zhangsq-nju/EdgeRazor)
- Inference: [ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp)

## Model Bit-Widths

| Mixed-Precision Recipe       | Bit-Width | This Repo | GGUF Type     |
| ---------------------------- | --------- | --------- | ------------- |
| 100% 4-bit + 0% 1.58-bit     | 4         | ✔️         | Q4_0          |
| 50% 4-bit + 50% 1.58-bit     | 2.79      | ✖️         | Not supported |
| 12.5% 4-bit + 87.5% 1.58-bit | 1.88      | ✖️         | Not supported |
| 0% 4-bit + 100% 1.58-bit     | 1.58      | ✔️         | TQ1_0, TQ2_0  |

## Get Started

Use llama.cpp to conduct efficient inference on edge devices.

Check the [cli.sh](./cli.sh) script for basic usage.

Model list:

- `Qwen3-1.7B-BF16.gguf`: BF16 model from the original Qwen3-1.7B
- `Qwen3-1.7B-EdgeRazor-Q4_0.gguf`: Q4_0 model from the [Qwen3-1.7B-EdgeRazor-4bit](https://huggingface.co/zhangsq-nju/Qwen3-1.7B-EdgeRazor-4bit)
- `Qwen3-1.7B-EdgeRazor-TQ1_0.gguf`: TQ1_0 model from [Qwen3-1.7B-EdgeRazor-1.58bit](https://huggingface.co/zhangsq-nju/Qwen3-1.7B-EdgeRazor-1.58bit)
- `Qwen3-1.7B-EdgeRazor-TQ2_0.gguf`: TQ2_0 model from [Qwen3-1.7B-EdgeRazor-1.58bit](https://huggingface.co/zhangsq-nju/Qwen3-1.7B-EdgeRazor-1.58bit)

## Citation

If you find our project useful in your research, please consider kindly citing our papers ✏️:

```
@article{zhangsh-edgerazor,
  title={{EdgeRazor}: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation},
  author={Shu-Hao Zhang and Le-Tong Huang and Xiang-Sheng Deng and Xin-Yi Zou and Chen Wu and Nan Li and Shao-Qun Zhang},
  year={2026},
  journal={arXiv preprint arXiv:2605.04062}
}
```