---
title: GLM-4.5-Air-AWQ
canonical_url: "https://www.modelscope.cn/models/cpatonn-mirror/GLM-4.5-Air-AWQ"
md_url: "https://www.modelscope.cn/models/cpatonn-mirror/GLM-4.5-Air-AWQ.md"
repository: cpatonn-mirror/GLM-4.5-Air-AWQ
last_updated: 2026-10-19
license: mit
pipeline_tag: text-generation
tasks:
- text-generation
model_type:
- glm4_moe
architectures:
- Glm4MoeForCausalLM
base_model:
- zai-org/GLM-4.5-Air
base_model_relation: quantized
parameters: 106.9B
tensor_type:
- I64
- I32
- BF16
- F32
library_name:
- safetensors
- pytorch
frameworks:
- pytorch
language:
- en
- zh
downloads: 841
stars: 2
---
# GLM-4.5-Air-AWQ
> GLM-4.5-Air-AWQ - cpatonn-mirror 在 ModelScope 开源的模型。Website cyan.kiwi Models Hugging Face · ModelScope Connect X · Reddit · Email
cpatonn-mirror/GLM-4.5-Air-AWQ 是 ModelScope 魔搭社区上的 106.9B 参数text-generation模型，采用 mit 许可，基于 zai-org/GLM-4.5-Air 构建。
- **Repository**: cpatonn-mirror/GLM-4.5-Air-AWQ
- **License**: mit
- **Tasks**: text-generation
- **Parameters**: 106.9B
- **Base model**: zai-org/GLM-4.5-Air
- **Downloads**: 841
- **Stars**: 2
- **Last updated**: 2026-10-19
Source: https://www.modelscope.cn/models/cpatonn-mirror/GLM-4.5-Air-AWQ
---
---
# GLM-4.5-Air
👋 Join our Discord community.
📖 Check out the GLM-4.5 technical blog, technical report, and Zhipu AI technical documentation.
📍 Use GLM-4.5 API services on Z.ai API Platform (Global) or
Zhipu AI Open Platform (Mainland China).
👉 One click to GLM-4.5.
## 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.
For more eval results, show cases, and technical details, please visit
our [technical blog](https://z.ai/blog/glm-4.5) or [technical report](https://huggingface.co/papers/2508.06471).
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
Please refer our [github page](https://github.com/zai-org/GLM-4.5) for more detail.
