workflow-templates-broken-zap-2026-06-08/site/knowledge/models/z-image.md

Z-Image

Z-Image is Zhipu AI's image generation model family, built on the CogView architecture with a hybrid autoregressive and diffusion decoder design.

Model Variants

GLM-Image (Z-Image)

• 9B autoregressive + 7B DiT diffusion decoder hybrid architecture
• First open-source industrial-grade discrete autoregressive image generator
• State-of-the-art bilingual text rendering (English and Chinese)

Z-Image-Turbo

• Optimized variant for faster inference with reduced latency
• Suitable for real-time and batch generation workflows

CogView-4

• 6B parameter DiT diffusion model, foundation for the Z-Image decoder

Key Features

• Industry-leading text rendering accuracy for posters and infographics
• Custom resolution from 512px to 2048px (multiples of 32)
• Image editing, style transfer, and identity-preserving generation
• LoRA training support; open weights on HuggingFace

Hardware Requirements

• Cloud API: no local hardware required ($0.015 per image via Z.ai)
• Self-hosted: 24GB+ VRAM for the combined 9B+7B architecture

Common Use Cases

• Text-to-image generation with accurate text rendering
• Commercial poster and graphic design
• Social media content creation
• Multi-subject consistency and identity-preserving generation

Key Parameters

• prompt: text description of the desired image
• size: output resolution (e.g., 1280x1280, 1568x1056, 960x1728)
• model: glm-image or cogview-4