MOSS-Image Studio: Layout-Aware Image Creation
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MOSS-Image

MOSS-Image turns detailed briefs and structured JSON into controlled renders, so you can position every object, caption and bounding box with precision.

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The Advantages of MOSS-Image

A five-billion-parameter image model that treats layout instructions as first-class input.

  • Direct Layout Guidance
    Assign a dedicated region to every object and text label, so the composition follows your JSON rather than model guesswork.
  • Five-Billion-Parameter Core, Long Context
    Extended prompts remain readable, while the same weights can be fine-tuned for specialized tasks and domains.
  • Two Checkpoints, One Architecture
    Both releases use Apache-2.0 licensing and the same structure; the SFT version produces cleaner whiteboard text.

Launch MOSS-Image in Three Steps

Go from Python setup to a precisely positioned image in three moves.

FAQ

Questions About MOSS-Image

Answers on prompts, model checkpoints and installation for MOSS-Image.

1

What can I define with layout control?

Your JSON describes the overall scene, individual objects and visible text, and assigns each element a position-and-size box.

2

What separates MOSS-Image-Base from MOSS-Image-SFT?

Both use the same architecture and sampling API. The SFT release is tuned on curated data and, in the project demo, delivers more coherent text grouping and a neater whiteboard arrangement.

3

What is the maximum prompt length for MOSS-Image?

It accepts as many as 4K tokens, which is ample for a multi-element layout JSON.

4

Which hardware and software are required?

You need Python 3.10 or newer plus an NVIDIA GPU and a compatible PyTorch build. When VRAM is constrained, use Sequential mode or lower the image size; Compile DiT stays off by default and cannot be used in that mode.

5

Is ComfyUI supported for MOSS-Image?

Yes. Find MOSS-Image in ComfyUI Manager, install the native plugin and open the sample workflow; official ComfyUI repository integration is still underway.

6

Which license covers the weights and code?

The model weights use Apache-2.0. Pipeline code and third-party components retain their respective licenses; cite the project repository for research work.

Put MOSS-Image to Work on Your Next Layout

Set up the Diffusers pipeline or ComfyUI plugin, test a structured layout prompt, or refine your concept with the MOSS-Image Prompt Enhancer.