GLM-Image
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Jan 14, 2026 12 min read

Mastering Text Rendering with GLM-Image: A Complete Guide

Learn how GLM-Image achieves exceptional text rendering accuracy with the Glyph-byT5 encoder, especially for Chinese characters.

Introduction

Text rendering in AI-generated images has long been a challenge for image generation models. Most models struggle with accurate text placement, correct spelling, and maintaining readability, especially for non-Latin scripts. GLM-Image addresses this challenge head-on with its innovative Glyph-byT5 text encoder, achieving remarkable accuracy rates of 0.9788 for Chinese text and 0.9557 for English text on the LongText-Bench benchmark.

In this comprehensive guide, you'll learn how GLM-Image's text rendering capabilities work, best practices for creating images with precise text integration, and real-world applications that benefit from this technology.

Understanding GLM-Image's Text Rendering Architecture

GLM-Image's exceptional text rendering performance stems from its unique architectural design that combines multiple innovations:

The Glyph-byT5 Text Encoder

At the heart of GLM-Image's text rendering capability is the Glyph-byT5 encoder. Unlike traditional text encoders that work at the word or token level, Glyph-byT5 operates at the character level, providing several key advantages:

  • Character-level precision: Each character is encoded individually, ensuring accurate representation of complex glyphs, especially important for Chinese, Japanese, and Korean characters.
  • Semantic understanding: The encoder maintains semantic relationships between characters while preserving visual accuracy.
  • Multi-script support: Handles multiple writing systems simultaneously without degradation in quality.

Integration with Hybrid Architecture

GLM-Image's 9B autoregressive generator works in tandem with the 7B diffusion decoder to render text accurately:

  1. The autoregressive component generates low-resolution tokens that establish text layout and positioning
  2. The diffusion decoder adds high-resolution details, ensuring crisp, readable text
  3. The Glyph-byT5 encoder guides both stages to maintain text accuracy throughout generation

Best Practices for Text Rendering

Prompt Engineering for Clear Text

To achieve optimal text rendering results with GLM-Image, follow these prompt engineering guidelines:

  • Be explicit: Clearly specify the exact text you want rendered in quotes
  • Provide context: Describe the text's purpose and placement in the image
  • Specify style: Mention font characteristics if important (bold, italic, decorative)

Example prompt: "A modern poster with the text 'Innovation Starts Here' in bold letters at the top, and '2026 Technology Summit' in smaller text below, on a gradient blue background"

Language-Specific Considerations

For Chinese text: GLM-Image excels at Chinese character rendering with 0.9788 accuracy. Specify traditional or simplified characters if needed, and consider character complexity when designing layouts.

For English text: With 0.9557 accuracy, GLM-Image handles English text exceptionally well. Pay attention to capitalization and punctuation in your prompts.

For multilingual content: GLM-Image can handle multiple languages in a single image. Clearly separate different language sections in your prompt.

Benchmark Analysis

GLM-Image's text rendering performance significantly outperforms competing models:

  • CVTG-2K Word Accuracy: 0.9116 (16.1% improvement over competitors)
  • LongText-Bench EN: 0.9557 (7.1% improvement)
  • LongText-Bench ZH: 0.9788 (13.2% improvement)

These benchmarks demonstrate GLM-Image's superiority in text rendering tasks, particularly for Chinese characters where the improvement is most pronounced.

Real-World Use Cases

Marketing Posters with Text

Create professional marketing materials with precise text integration. GLM-Image ensures your promotional text is clear, readable, and visually appealing.

Infographics and Data Visualization

Generate infographics with accurate labels, statistics, and explanatory text. The model's knowledge-intensive generation capabilities combine with text rendering for informative visuals.

Multilingual Educational Materials

Produce educational content in multiple languages with consistent quality. Particularly valuable for Chinese-English bilingual materials where GLM-Image's dual-language strength shines.

Advanced Techniques

Combining Text with Complex Backgrounds

GLM-Image maintains text readability even against complex backgrounds. Use descriptive prompts to specify text contrast and positioning for optimal results.

Multiple Text Elements

When including multiple text elements, structure your prompt hierarchically, specifying primary and secondary text with clear positioning instructions.

Conclusion

GLM-Image's text rendering capabilities represent a significant advancement in AI image generation. With the Glyph-byT5 encoder and hybrid architecture, it achieves unprecedented accuracy in text rendering, especially for Chinese characters. By following the best practices outlined in this guide, you can leverage GLM-Image to create professional-quality images with precise text integration for your projects.

Ready to try GLM-Image's text rendering capabilities? Start creating now with our free demo.