GLM-Image

Qwen-Image 2.0 is the latest AI image generation and editing model in the Qwen family that combines both generation and editing in a single unified architecture, delivering high-quality visuals with professional-grade typography and layout capabilities directly from natural-language prompts. It supports text-to-image and image editing workflows with a lightweight 7 billion-parameter model that runs quickly while producing native 2048x2048 resolution outputs and handling long, detailed instructions up to about 1,000 tokens so creators can generate complex infographics, posters, slides, comics, and photorealistic scenes with accurate, well-rendered English and other language text embedded in the visuals. The unified model design means users don’t need separate tools for creating and modifying images, making it easier to iterate on ideas and refine compositions.

ERNIE-Image is an open text-to-image generation model developed by Baidu, designed to deliver high-quality visuals with strong instruction accuracy and controllability. It is built on a single-stream Diffusion Transformer (DiT) architecture with around 8 billion parameters, allowing it to achieve state-of-the-art performance among open-weight image models while remaining relatively efficient. The model includes a built-in prompt enhancement system that expands simple user inputs into richer, structured descriptions, improving the quality and consistency of generated images. ERNIE-Image is optimized for complex instruction following, enabling accurate rendering of text within images, structured layouts, and multi-element compositions, making it particularly suitable for use cases like posters, comics, and multi-panel designs. It supports multilingual prompts, including English, Chinese, and Japanese, broadening accessibility and usability across regions.