MODEL PROFILE

glm-4-9b-chat-hf

zai-org · glm-4-9b-chat-hf

GLM-4-9B is the open-source version of the latest generation of pre-trained models in the GLM-4 series launched by Zhipu AI. In the evaluation of data sets in semantics, mathematics, reasoning, code, and knowledge, **GLM-4-9B** and its human preference-aligned version **GLM-4-9B-Chat** have shown superior performance beyond Llama-3-8B. In addition to multi-round conversations, GLM-4-9B-Chat also has advanced features such as web browsing, code execution, custom tool calls (Function Call), and long context reasoning (supporting up to 128K context). This generation of models has added multi-language support, supporting 26 languages including Japanese, Korean, and German. We have also launched the **GLM-4-9B-Chat-1M** model that supports 1M context length (about 2 million Chinese characters) and the multimodal model GLM-4V-9B based on GLM-4-9B. **GLM-4V-9B** possesses dialogue capabilities in both Chinese and English at a high resolution of 1120*1120. In various multimodal evaluations, including comprehensive abilities in Chinese and English, perception & reasoning, text recognition, and chart understanding, GLM-4V-9B demonstrates superior performance compared to GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max, and Claude 3 Opus. The eval_needle experiment was conducted with a context length of 1M, and the results are as follows: The tests for GLM-4-9B-Chat and Llama-3-8B-Instruct are conducted on six multilingual datasets. The test results and the corresponding languages selected for each dataset are shown in the table below:

Text generationlicense:other
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/2 19:16:08
OVERVIEW

Model overview

GLM-4-9B is the open-source version of the latest generation of pre-trained models in the GLM-4 series launched by Zhipu AI. In the evaluation of data sets in semantics, mathematics, reasoning, code, and knowledge, **GLM-4-9B** and its human preference-aligned version **GLM-4-9B-Chat** have shown superior performance beyond Llama-3-8B. In addition to multi-round conversations, GLM-4-9B-Chat also has advanced features such as web browsing, code execution, custom tool calls (Function Call), and long context reasoning (supporting up to 128K context). This generation of models has added multi-language support, supporting 26 languages including Japanese, Korean, and German. We have also launched the **GLM-4-9B-Chat-1M** model that supports 1M context length (about 2 million Chinese characters) and the multimodal model GLM-4V-9B based on GLM-4-9B. **GLM-4V-9B** possesses dialogue capabilities in both Chinese and English at a high resolution of 1120*1120. In various multimodal evaluations, including comprehensive abilities in Chinese and English, perception & reasoning, text recognition, and chart understanding, GLM-4V-9B demonstrates superior performance compared to GPT-4-turbo-2024-04-09, Gemini 1.0 Pro, Qwen-VL-Max, and Claude 3 Opus. The eval_needle experiment was conducted with a context length of 1M, and the results are as follows: The tests for GLM-4-9B-Chat and Llama-3-8B-Instruct are conducted on six multilingual datasets. The test results and the corresponding languages selected for each dataset are shown in the table below:

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。