GLM-4 Series

Open-source multilingual multimodal dialogue model

EditorRecommendationProgrammingMultilingualMultimodal

GLM-4 Series is the next-generation pre-trained model launched by Zhipu AI, including GLM-4-9B, GLM-4-9B-Chat, GLM-4-9B-Chat-1M, and GLM-4V-9B. These models excel in semantic understanding, mathematical reasoning, code execution, and support up to 26 languages. They also possess advanced functionalities like web browsing and code execution. The GLM-4V-9B model boasts high-resolution visual understanding capabilities, making it suitable for multimodal applications.

Multi-turn dialogue capability
supporting long-text reasoning
with a maximum context length of 128K.
Web browsing functionality
capable of parsing and understanding webpage content.
Code execution functionality
able to run and understand code.
Custom tool invocation
allowing integration of external tools and APIs.
Multi-language support

Target audience includes developers
data scientists
and AI researchers who can utilize the GLM-4 series models for natural language processing
machine learning
and other AI-related research and development. The multilingual and multimodal capabilities of these models are particularly suited for international projects requiring handling of multiple languages and visual data.

Develop a cross-language chatbot using GLM-4-9B-Chat.
Perform multimodal data analysis combining images and text using GLM-4V-9B.
Conduct semantic analysis and knowledge discovery of large-scale text corpora using the GLM-4 series models.

Step 1: Visit the GLM-4 series model's GitHub page to understand the model's basic information and features.
Step 2: Select a suitable model version based on your needs
such as GLM-4-9B or GLM-4V-9B.
Step 3: Read the documentation to learn how to download and deploy the model.
Step 4: Start building your application using the provided example code or API.

Visit

GLM-4 Series Visit Over Time

Monthly Visits

490881889

Bounce Rate

37.92%

Page per Visit

5.6

Visit Duration

00:06:18

GLM-4 Series Visit Trend

GLM-4 Series Visit Geography

GLM-4 Series Traffic Sources

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GLM-4 Series

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GLM-4 Series Visit Trend

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