Tasks and inputs
Ming Image 0.1 Design is listed for Text-to-image. It accepts text and produces image. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 8, 2026
Ming Image 0.1 Design generates interface visuals, infographics and graphic compositions, including transparent RGBA images.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
Ming Image 0.1 Design generates interface visuals, infographics and graphic compositions, including transparent RGBA images.
Ming Image 0.1 Design is a 6B text-to-image model aimed at UI visuals, infographics and composed designs. It supports RGBA output, making a transparent asset a documented capability of the model rather than a background-removal step inferred from a generic image generator.
Specify the elements, their hierarchy, the intended placement and any text that must be readable. For a UI illustration, separate the visual concept from functional controls that still need to be implemented in the application. Check the generated asset at its intended display size, especially small lettering and dense information.
The companion Ming Image repository supplies installation and inference instructions. Supported resolution buckets include 1024 and 2048. A separate prompt-enhancement model can rewrite a short brief before generation, so preserve both the original request and the rewritten prompt when comparing results.
Inspect the alpha channel, edge quality and whether empty areas are truly transparent. Confirm that the composition leaves the space needed for surrounding page content. Keep editable source material when available, since a flat generated graphic still needs changes during a design review. The weights use the MIT licence; local GPU and runtime costs are separate from downloadable access.
Compare the model on the work you need to complete.
Ming Image 0.1 Design is listed for Text-to-image. It accepts text and produces image. Use the publisher’s input format and preprocessing for your chosen deployment.
Choose the output size and quality your design needs. Include drafts and revisions when budgeting an accepted image.
The weights are downloadable under MIT. Check runtime support and size the complete model and working context for your expected concurrency.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
Alibaba
Qwen-Image-2.1-Turbo creates and edits images, including reference-guided and transparency workflows; hosted billing is separate from local deployment.
Alibaba
Qwen-Image-2.1-Pro creates and edits images, including reference-guided and transparency workflows; hosted billing is separate from local deployment.
Meta
Muse Image 1.0 generates and edits images through conversational or single-shot endpoints, with flat per-image Meta Model API billing.
krea
Krea 2 Raw: a base checkpoint for further training, not the recommended everyday inference release.
krea
Krea 2 Turbo: the post-trained and distilled Krea 2 checkpoint for image generation.
OpenAI
GPT-5.4 Image 2 from OpenAI: Image model for prompt-driven generation, editing, and visual design workflows.