Ming Image Design

Ming-Image-0.1-Design is a 6B text-to-image model built for visual design work: UI mockups, infographics, posters, slides and anything else where the text has to come out right. It renders legible type as part of the composition instead of the usual generative-model scribble, and it can output RGBA with a transparent background.

Originally released by inclusionAI on Hugging Face under the MIT license. All credit for the model goes to the inclusionAI team. Civitai is hosting a mirror so creators can run it on-site without a local install - please head to the original repository for weights, updates and to follow the project directly.

Built by

• inclusionAI - the Ming-Image series and the Ling-mini-2.0 text encoder it runs on
• The Ming-Image repository - reference inference code, prompt rewriting and the layer-decomposition demo
• Comfy-Org - the repackaged single-file weights this mirror is built from

Text-rich design, not just pictures

The model was trained for complete visual compositions rather than single subjects. Prompts that describe a layout - headings, body copy, callouts, spacing - are what it is built to answer, and it places readable text inside that layout. It sits near the top of the Artificial Analysis UI/UX design leaderboard.

Transparent backgrounds

Ming-Image-0.1-Design generates RGBA output with genuine alpha, so a logo, sticker or UI element comes out ready to composite. Upstream recommends prepending one of the RGBA trigger phrases documented in the transparent-background tip to switch it on.

Recommended settings

• Resolution: 2048 x 2048 for best quality, 1024 x 1024 for speed. Output is square at the selected bucket.
• Steps: 12.
• CFG scale: 1.0. Negative prompts do nothing at CFG 1.
• Precision: BF16.

Upstream also suggests running prompts through a rewriter first - Ling-3.0-flash-VL or a comparable VLM - since the model responds well to long, structured design briefs.

The Layer model

The series has a second 6B model, Ming-Image-0.1-Design-Layer, which takes a flattened design and splits it back into separate transparent layers you can edit. It is a different checkpoint with its own task and is not part of this model page.

Links

• Source: inclusionAI/Ming-Image-0.1-Design on Hugging Face
• Code: github.com/inclusionAI/Ming-Image
• ModelScope: inclusionAI/Ming-Image-0.1-Design
• Demo: Hugging Face Space
• Agent skills: Ling UI Design and Image to Editable PPT