---
title: codegeex4-all-9b-GGUF
canonical_url: "https://www.modelscope.cn/models/ZhipuAI/codegeex4-all-9b-GGUF"
md_url: "https://www.modelscope.cn/models/ZhipuAI/codegeex4-all-9b-GGUF.md"
repository: ZhipuAI/codegeex4-all-9b-GGUF
last_updated: 2026-07-18
license: other
pipeline_tag: text-generation
tasks:
  - text-generation
library_name:
  - gguf
  - pytorch
frameworks:
  - Pytorch
language:
  - zh
  - en
downloads: 3009
stars: 20
tags:
  - glm
  - codegeex
  - thudm
  - gguf
---

# codegeex4-all-9b-GGUF

> codegeex4-all-9b-GGUF - ZhipuAI 在 ModelScope 开源的模型。我们推出了 CodeGeeX4-ALL-9B，这是最新的 CodeGeeX4 系列模型的开源版本。该模型是在 GLM-4-9B 基础上持续训练的多语言代码生成模型，显著提升了代码生成能力。使用单个 CodeGeeX4-ALL-9B 模型，可以支持代码补全与生成、代码解释、联网搜索、函数调用、仓库级代码问答等多种功能，覆盖了软件开发的各个场景。CodeGeeX4-ALL-9B 在 BigCodeBench 和…

ZhipuAI/codegeex4-all-9b-GGUF 是 ModelScope 魔搭社区上的text-generation模型，采用 other 许可。

- **Repository**: ZhipuAI/codegeex4-all-9b-GGUF
- **License**: other
- **Tasks**: text-generation
- **Tags**: glm, codegeex, thudm, gguf
- **Downloads**: 3009
- **Stars**: 20
- **Last updated**: 2026-07-18

Source: https://www.modelscope.cn/models/ZhipuAI/codegeex4-all-9b-GGUF

---

# CodeGeeX4: Open Multilingual Code Generation Model

<center>
    <img src="https://raw.githubusercontent.com/THUDM/CodeGeeX4/main/resources/logo.jpeg" alt="CodeGeeX4">
</center>

[中文](./README_zh.md)

[GitHub](https://github.com/THUDM/CodeGeeX4)

!!! This is the GGUF version of CodeGeeX4, the original version can be found [here](https://huggingface.co/THUDM/codegeex4-all-9b). !!!

We introduce CodeGeeX4-ALL-9B, the open-source version of the latest CodeGeeX4 model series. It is a multilingual code generation model continually trained on the [GLM-4-9B](https://github.com/THUDM/GLM-4), significantly enhancing its code generation capabilities. Using a single CodeGeeX4-ALL-9B model, it can support comprehensive functions such as code completion and generation, code interpreter, web search, function call, repository-level code Q&A, covering various scenarios of software development. CodeGeeX4-ALL-9B has achieved highly competitive performance  on public benchmarks, such as [BigCodeBench](https://huggingface.co/datasets/bigcode/bigcodebench) and [NaturalCodeBench](https://github.com/THUDM/NaturalCodeBench). It is currently the most powerful code generation model with less than 10B parameters, even surpassing much larger general-purpose models, achieving the best balance in terms of inference speed and model performance.

## Get Started

Download model weights:
```
huggingface-cli download THUDM/codegeex4-all-9b-GGUF 
```

Use the latest llama.cpp to launch codegeex4-all-9b-GGUF
```
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake . -B build
cmake --build build --config Release
build/bin/llama-cli -m Your_Model_Path -p "Your_Input"
```

Please make sure the prompt is under the following format:
```
f"<|system|>\n{system_prompt}\n<|user|>\n{prompt}\n<|assistant|>\n"
```
Default system_prompt:
```
你是一位智能编程助手，你叫CodeGeeX。你会为用户回答关于编程、代码、计算机方面的任何问题，并提供格式规范、可以执行、准确安全的代码，并在必要时提供详细的解释。
```
The English version:
```
You are an intelligent programming assistant named CodeGeeX. You will answer any questions users have about programming, coding, and computers, and provide code that is formatted correctly.
```

## Evaluation

| **Model**                   | **Seq Length** | **HumanEval** | **MBPP** | **NCB** | **LCB** | **HumanEvalFIM** | **CRUXEval-O** |
|-----------------------------|----------------|---------------|----------|---------|---------|------------------|----------------|
| Llama3-70B-intruct          | 8K             | 77.4          | 82.3     | 37.0    | 27.4    | -                | -              |
| DeepSeek Coder 33B Instruct | 16K            | 81.1          | 80.4     | 39.3    | 29.3    | 78.2             | 49.9           |
| Codestral-22B               | 32K            | 81.1          | 78.2     | 46.0    | 35.3    | 91.6             | 51.3           |
| CodeGeeX4-All-9B            | 128K           | 82.3          | 75.7     | 40.4    | 28.5    | 85.0             | 47.1           |

## License

The model weights are licensed under the following [License](./LICENSE).

## Citation

If you find our work helpful, please feel free to cite the following paper:

```
@inproceedings{zheng2023codegeex,
  title={CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X},
  author={Qinkai Zheng and Xiao Xia and Xu Zou and Yuxiao Dong and Shan Wang and Yufei Xue and Zihan Wang and Lei Shen and Andi Wang and Yang Li and Teng Su and Zhilin Yang and Jie Tang},
  booktitle={Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages={5673--5684},
  year={2023}
}
```