Model Details
Uni-1 is the standard tier of the Uni-1 family and the sensible default for text-to-image work: give it a prompt and it returns a single, polished image, generated faster and more cheaply than the Max tier. It carries the full Uni-1 feature set — `auto` or `manga` styling, optional web-grounded references, and up to nine reference images to steer the result — so you trade only headroom on the very hardest prompts, not capability. Reach for it whenever you want a strong result without paying for a hero-grade render.
## Best for - Everyday single images and quick iteration where cost and speed matter - Faithful rendering of clear, specific prompts at any of the supported aspect ratios - Black-and-white manga and comic line-art via the `manga` style - Illustrations that should reflect real, recent, or niche subjects using web-grounded references - Generations steered by your own reference images for composition, subject, or style
## Choose another model when - You need maximum fidelity and the strongest prompt adherence on a single hero shot and can accept higher cost — use `luma/uni-1-max` - You want to edit or transform an existing image rather than generate one from a prompt — use an image-to-image or image-editing model - You need motion or video output — use a video model
## Tips - Write clear, specific prompts; this tier rewards precise wording. - Use `manga` only when you want inked line-art — `auto` covers photoreal and most illustrative looks. - Step up to `luma/uni-1-max` when one hero image needs the highest possible detail.
## Advanced Configuration - `style` — `auto` (default) picks a fitting photoreal or illustrative look; `manga` produces black-and-white manga / comic line-art for paneled illustration and inked characters. - `enable_web_search` — set `true` to let the model consult the web for visual references while generating, useful when your prompt names real, recent, or niche subjects; leave `false` (default) for faster, self-contained generation. - `reference_image_urls` — pass up to nine image URLs to guide composition, subject, or style toward your own references; the model blends them with the prompt.
To run via the ModelRunner JavaScript client: ```js import { modelrunner } from "@modelrunner/client";
const result = await modelrunner.subscribe("luma/uni-1", { input: { prompt: "a lighthouse on a cliff at golden hour, dramatic sky", aspect_ratio: "16:9", style: "auto", }, }); ```





