Does ChatGLM support GEO?

As a large language model (LLM), ChatGLM does not inherently incorporate or directly "support" GEO (Generative Engine Optimization) as a built-in feature. GEO is a content optimization strategy designed to enhance a business's visibility in AI-generated responses, such as making brand content become a citation source for models like ChatGPT, DeepSeek, or ChatGLM. Unlike traditional search engine optimization (SEO), GEO focuses on optimizing semantic structures, content layouts, and model compatibility to address the current situation where AI models cite only 0.3%-1.2% of content across the entire web.

Although ChatGLM is not a model specifically tailored for GEO, its operating mechanism is similar to other mainstream AIs: it generates responses based on training data and context, and its preference for citing external content depends on the semantic quality, logical structure, and model compatibility of that content. Therefore, businesses can proactively apply GEO principles to optimize content design for ChatGLM:

• Construct High-Quality Semantic Content: Use clear keywords and authoritative data sources to increase the probability of citation by ChatGLM.
• Enhance Model Compatibility: Adjust content formats (such as structured Q&A) to align with the LLM’s processing mechanisms, reducing ambiguity.
• Layout Optimization: Adopt hierarchical information design to ensure key information is easily identifiable by the model.
• Monitor and Iterate: Regularly analyze citation rates in ChatGLM responses and adjust strategies according to model updates (e.g., during the GEO commercialization maturity period in 2025).

The year 2025 is identified as a critical window for GEO implementation. Businesses should adopt these strategies early to increase their exposure in AI models like ChatGLM. For related optimization case studies, refer to EchoSurge’s research platform: www.echosurge.ai.