| | --- |
| | license: mit |
| | language: |
| | - en |
| | - zh |
| | pipeline_tag: text-generation |
| | library_name: transformers |
| | --- |
| | |
| | # GLM-4.5-Air-Base |
| |
|
| | <div align="center"> |
| | <img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/> |
| | </div> |
| | <p align="center"> |
| | 👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community. |
| | <br> |
| | 📖 Check out the GLM-4.5 <a href="https://z.ai/blog/glm-4.5" target="_blank">technical blog</a>, <a href="https://arxiv.org/abs/2508.06471" target="_blank">technical report</a>, and <a href="https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D" target="_blank">Zhipu AI technical documentation</a>. |
| | <br> |
| | 📍 Use GLM-4.5 API services on <a href="https://docs.bigmodel.cn/cn/guide/models/text/glm-4.5">Zhipu AI Open Platform</a>. |
| | <br> |
| | 👉 One click to <a href="https://chat.z.ai">GLM-4.5</a>. |
| | </p> |
| | |
| | ## Model Introduction |
| | |
| | The **GLM-4.5** series models are foundation models designed for intelligent agents. GLM-4.5 has **355** billion total parameters with **32** billion active parameters, while GLM-4.5-Air adopts a more compact design with **106** billion total parameters and **12** billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications. |
| |
|
| | Both GLM-4.5 and GLM-4.5-Air are hybrid reasoning models that provide two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses. |
| |
|
| | We have open-sourced the base models, hybrid reasoning models, and FP8 versions of the hybrid reasoning models for both GLM-4.5 and GLM-4.5-Air. They are released under the MIT open-source license and can be used commercially and for secondary development. |
| |
|
| | As demonstrated in our comprehensive evaluation across 12 industry-standard benchmarks, GLM-4.5 achieves exceptional performance with a score of **63.2**, in the **3rd** place among all the proprietary and open-source models. Notably, GLM-4.5-Air delivers competitive results at **59.8** while maintaining superior efficiency. |
| |
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| |  |
| |
|
| | For more eval results, show cases, and technical details, please visit |
| | our [technical blog](https://z.ai/blog/glm-4.5). The technical report will be released soon. |
| |
|
| | The model code, tool parser and reasoning parser can be found in the implementation of [transformers](https://github.com/huggingface/transformers/tree/main/src/transformers/models/glm4_moe), [vLLM](https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/models/glm4_moe_mtp.py) and [SGLang](https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/models/glm4_moe.py). |
| |
|
| | ## Quick Start |
| |
|
| | **Note**: This is a base model, not for chat. |
| |
|
| | Please refer to our [github page](https://github.com/zai-org/GLM-4.5) for more details. |
| |
|
