Luma Uni V1 Text To Image

Luma Uni V1 Text To Image

Playground

Luma Uni v1 Text to Image is a fast AI image generation model that creates high-fidelity images from prompts with flexible aspect ratios, visual style control, and optional reference-image guidance. Ready-to-use REST inference API for creative design, marketing visuals, product mockups, brand assets, social media content, concept art, and professional text-to-image workflows with simple integration, no coldstarts, and affordable pricing.

Features

Luma UNI V1 Text-to-Image

Luma UNI V1 Text-to-Image generates images from natural-language prompts with optional reference-image guidance, flexible aspect ratios, and selectable output formats. It is suitable for concept art, stylized marketing visuals, sci-fi scenes, product ideas, and other prompt-driven image generation workflows.

Why Choose This?

• Prompt-based image generation
  Turn natural-language descriptions into polished visual outputs.

• Optional reference-image guidance
  Add one or more reference images when you want stronger visual steering.

• Flexible aspect ratios
  Choose a size preset that fits square, portrait, or landscape layouts.

• Simple workflow
  Write a prompt, choose a size, optionally add references, and generate the final image.

• Production-ready API
  Suitable for creative ideation, social visuals, campaign drafts, and design exploration.

Parameters

How to Use

1. Write your prompt — describe the subject, environment, lighting, composition, and mood you want.
2. Choose size (optional) — select the aspect ratio that best fits your intended output.
3. Choose output format (optional) — select the file format that best fits your workflow.
4. Add references (optional) — upload one or more reference images if you want stronger style or subject guidance.
5. Submit — run the model and download the generated image.

Example Prompt

A futuristic cyberpunk megacity at night, towering skyscrapers covered with holographic advertisements, flying vehicles, wet streets reflecting neon lights, dense atmosphere, cinematic lighting, ultra detailed, realistic, 35mm photography, high contrast, volumetric fog, 16:9

Pricing

Pricing includes a fixed base image charge plus an extra fee for each reference image.

Billing Rules

• Every request starts with a base price of $0.042 per image
• Each added reference image adds $0.003
• size and output_format do not affect pricing

Best Use Cases

• Concept art — Explore visual directions and scene ideas quickly.
• Style-guided generation — Use references when you want the output closer to a target visual language.
• Marketing creatives — Generate campaign visuals, social graphics, and concept ads.
• Product ideation — Produce stylized product or environment concepts from prompts.
• Creative prototyping — Quickly compare prompt-only and reference-guided outputs.

Pro Tips

• Use reference images only when you want stronger control, since they increase the price slightly.
• Keep prompts specific about subject, lighting, mood, and scene composition.
• Use jpeg for lightweight delivery unless your workflow requires a different format.
• Start without references first, then add them only if you need extra guidance.
• Match the prompt and references in style if you want a more coherent result.

Notes

• prompt is required.
• Pricing depends on the number of reference images.
• The returned result is a generated image.
• Better prompts usually improve visual coherence and controllability.

Related Models

• Luma image generation workflows — Useful when you need different generation styles or model behavior.
• Prompt-based image generation models — Useful when you want alternative quality, cost, or visual tradeoffs.

<ApiPage model={model}>
  ## Authentication

  For authentication details, please refer to the [Authentication Guide](/docs-authentication).

  ## API Endpoints

  ### Submit Task & Query Result

  ## Parameters

  ### Task Submission Parameters

  #### Request Parameters

  #### Response Parameters

  <SubmitResponse />

  #### Result Request Parameters

  | Parameter | Type | Required | Default | Description |
  |-----------|------|----------|---------|-------------|
  | id | string | Yes | - | Task ID |

  #### Result Response Parameters

  | Parameter | Type | Description |
  |-----------|------|-------------|
  | code | integer | HTTP status code (e.g., 200 for success) |
  | message | string | Status message (e.g., "success") |
  | data | object | The prediction data object containing all details |
  | data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
  | data.model | string | Model ID used for the prediction |
  | data.outputs | string | Array of URLs to the generated content. |
  | data.urls | object | Object containing related API endpoints |
  | data.urls.get | string | URL to retrieve the prediction result |
  | data.status | string | Status of the task: `created`, `processing`, `completed`, or `failed` |
  | data.created_at | string | ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z") |
  | data.error | string | Error message (empty if no error occurred) |
  | data.timings | object | Object containing timing details |
  | data.timings.inference | integer | Inference time in milliseconds |

</ApiPage>