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GLM-Image
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GLM-Image

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GLM-Image: Generate and Edit Images with Clean, Readable Text


GLM-Image is Z.ai’s flagship open-source image model built for creators who need images that communicate, not just look pretty. It uses a hybrid “autoregressive + diffusion decoder” design that’s especially strong at instruction following, detail control, and generating knowledge-heavy visuals like posters, slides, and infographic-style layouts.

💕Why Creators Love It

· Sharp Prompt Understanding: The AR module is initialized from GLM-4-9B-0414, helping it stay aligned with complex instructions.

· Crisp High-Res Output: A diffusion decoder based on a single-stream DiT architecture helps refine details and structure.

· Better Text in Images: The decoder includes a Glyph Encoder module to improve accurate text rendering inside images.

🔧More Than Text-to-Image: It Can Edit Images Too

GLM-Image supports a rich set of image-to-image workflows, including:

· Image editing (instruction-based changes).

· Style transfer.

· Identity-preserving generation.

· Multi-subject consistency.

💡What You Can Do with It on SeaArt AI

Generate: posters, covers, thumbnails, product mockups, UI concepts, diagrams, sci-pop visuals, and anything with structured layout.
Edit: upload an image and ask for changes like “replace background”, “change outfit”, “make it cinematic”, “keep the same character but swap the scene”.

▶️Quick Start on SeaArt AI

1. Choose GLM-Image in the model list.

2. Pick Text to Image to generate, or Image Editing to upload and transform.

3. Write a clear prompt, add layout details if needed, then generate.

📍Prompt tips for best results· Put any exact on-image text in quotes, and specify placement (top headline, center title, footer).

· Describe layout like a designer: grid, margins, typography, negative space.

· For edits, say what to keep and what to change: “keep face and pose, change background to…”

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2026-01-23
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2026-01-23
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Checkpoint
Data di pubblicazione
2026-01-23
Modello Base
GLM-Image
Model Parameters
clip_skip:1
Parametri di Allenamento
Epochs:1
Steps:0
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