GLM Image

GLM Image is an advanced image generation model that combines autoregressive and diffusion decoder technologies to produce high-quality visual content from text descriptions. The model employs a hybrid architecture featuring a 9-billion-parameter autoregressive component and a 7-billion-parameter diffusion decoder, enabling it to balance semantic understanding with precise visual detail rendering.

The application excels in text-to-image generation, particularly for knowledge-intensive scenarios such as presentations, infographics, posters, and scientific diagrams. Its specialized Glyph Encoder module delivers accurate text rendering within images, including support for complex scripts like Chinese characters. This capability addresses a common limitation in image generation where text accuracy is often compromised.

Beyond text-to-image creation, GLM Image supports a comprehensive range of image-to-image tasks within a single unified model. These include image editing, style transfer, identity-preserving generation for people and objects, and multi-subject consistency for applications like e-commerce displays and multi-panel narratives. This versatility makes it suitable for diverse creative and commercial applications requiring consistent visual output across multiple contexts.

The model's architecture addresses specific challenges in generating complex visual content by separating instruction understanding from detail rendering. The autoregressive module processes overall composition and semantic alignment, while the diffusion decoder handles high-frequency details and text accuracy. This decoupled approach enables stronger adherence to complex instructions compared to standard latent diffusion models.

GLM Image has achieved state-of-the-art performance in open-source benchmarks for text rendering, ranking first among open-source models on the CVTG-2K (Complex Visual Text Generation) leaderboard with a Word Accuracy score of 0.9116. This performance metric demonstrates its capability in handling multiple text instances across different image regions with high precision.

The model is available as an open-source release, enabling independent deployment and integration into various applications and workflows. Its design prioritizes both visual fidelity and semantic comprehension, making it suitable for scenarios requiring accurate information visualization alongside aesthetic quality.

Website: glmimageai.ai

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