Description
GLM-Image is an AI-driven image creation model by zai-org, employing a combined autoregressive and diffusion decoder setup. While matching the quality of standard latent diffusion methods for general image creation, it particularly excels where text-rendering and knowledge-based generation are important.
It shows strong performance in areas needing in-depth semantic understanding and detailed information expression, while maintaining high-quality and detailed image creation.
The architecture includes a 9B-parameter autoregressive generator, starting from GLM-4-9B-0414 with added visual tokens, a diffusion decoder, and a post-training system using the GRPO reinforcement learning algorithm to improve both semantic understanding and visual detail quality.
GLM-Image can handle both text-to-image and image-to-image creation. It's capable of producing highly detailed images from text descriptions and enables various image-to-image functions like image modification, style changes, consistent subject generation, and identity-preserving creation.
Pricing Plans
Releases
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Pros & Cons
Pros
Combined autoregressive design
Diffusion decoding
Text-rendering features
Cons
Requires GPU with 80GB+ of memory
Image resolution must be evenly divisible by 32
High cost for execution
