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MOSS-Image goes open source with bilingual text rendering and experimental layout control
- Who
- vLLM
- What
- supported the MOSS-Image open-source release with vLLM-Omni
What happened
MosiAI announced the open-source release of MOSS-Image, built on a 5B Diffusion Transformer (DiT), with Chinese and English text rendering, up to 4K-token prompts, and experimental JSON layout control using bounding boxes. Base and SFT checkpoints are available on Hugging Face, alongside open model weights and Apache-2.0 licensed inference code. vLLM congratulated the team and announced Day-0 support through vLLM-Omni.
Why it matters
The release provides a concrete example of combining bilingual text rendering with experimental bounding box layout control, giving developers a reference for image generation workflows that require explicit text and object placement.
The story so far
MosiAI released MOSS-Image’s model weights and inference code, with Base and SFT checkpoints available on Hugging Face, while vLLM announced Day-0 support through vLLM-Omni. The inference code is licensed under Apache-2.0. Built on a 5B Diffusion Transformer (DiT), MOSS-Image supports Chinese and English text rendering and prompts of up to 4K tokens. It also offers experimental JSON layout control using bounding boxes.
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