Paper page - MOSS-Image Technical Report

Source: https://huggingface.co/papers/2610.23374 Published on Oct 16

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Submitted byhttps://huggingface.co/Phospheneser

Xu Zheon Oct 19

Abstract

MOSS-Image is an open diffusion transformer that combines high-fidelity synthesis with intent-aware prompt enhancement to generate text-rich, layout-coherent images, achieving state-of-the-art open-weight results on long-form text and layout benchmarks.

Recent closed-source image generation systems can produce diverse visual content from simple compositions to information-dense graphics, yet open-weight text-to-image models still struggle with dense text and intricate layouts. To narrow this gap, we introduce MOSS-Image, an open generation system that combines high-fidelity visual synthesis with intent-aware composition. First, we pretrain a 5Bsingle-stream diffusion transformer(DiT) from scratch with a carefully designed recipe, enablingbilingual long-form text renderingand preciselayout control. Second, we develop anintention-aware agentic prompt enhancement(PE) module that translates diverse user requests into detailed content and layout specifications. Together, they enable MOSS-Image to generate text-rich and layout-coherent images. We further introduceLongLongTextBench(LLTB) for evaluating long-form English and Chinese text rendering, andRealLayoutArena(RLA) for end-to-end layout-rich generation. MOSS-Image achieves state-of-the-art performance among open-weight models on LLTB, with an average text coverage of 96.3%. On RLA, MOSS-Image ranks second in the end-to-end system comparison, while its backbone ranks first among generators evaluated with shared enhanced prompts. We will release the model, training recipe, and evaluation framework to support further research and promote the text-to-image community.

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#### OpenMOSS-Team/MOSS-Image-SFT Text-to-Image• 5B• Updatedabout 3 hours ago • 2.09k • 364 #### OpenMOSS-Team/MOSS-Image-Base Text-to-Image• 5B• Updatedabout 3 hours ago • 1.79k • 318

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