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  ---
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- license: apache-2.0
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  language:
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  - en
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  - zh
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  pipeline_tag: text-generation
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  library_name: transformers
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: mit
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  language:
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  - en
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  - zh
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  pipeline_tag: text-generation
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  library_name: transformers
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+ ---
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+
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+ # GLM-4.5-Air-Base
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+
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+ <div align="center">
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+ <img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/>
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+ </div>
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+ <p align="center">
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+ 👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
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+ <br>
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+ 📖 Check out the GLM-4.5 <a href="https://z.ai/blog/glm-4.5" target="_blank">technical blog</a>.
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+ <br>
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+ 📍 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>.
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+ <br>
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+ 👉 One click to <a href="https://chat.z.ai">GLM-4.5</a>.
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+ </p>
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+
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+ ## Model Introduction
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+ 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.
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+ 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.
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+ 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.
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+ 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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+ ![bench](https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/bench.png)
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+ For more eval results, show cases, and technical details, please visit our [technical report](https://z.ai/blog/glm-4.5).
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+ 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).
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+ ## Quick Start
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+ **Note**: This model is based Model, not for chat.
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+ Please refer our [github page](https://github.com/zai-org/GLM-4.5) for more detail.