flux-pro is the image creation entry point for the Black Forest Labs FLUX Pro series, designed to turn clear text concepts into visual assets that emphasize detail, composition, and style. On this platform, it supports text-to-image generation and can also edit existing images using text instructions, making it suitable for marketing concept art, product scene drafts, and illustration exploration, with multiple aspect ratios and asynchronous task processing options.
Submit requests to the public API at api.acedata.cloud using the documented parameters, then use the results in your application.
api.acedata.cloudflux-proInput parameters and result formats vary by service. Use the public API for this model and follow its guide for generation, task retrieval and editing operations.
The FLUX Pro series excels at prompt adherence and visual detail; the dimensions, operations, and result formats above apply to the flux-pro entry point on this platform.
flux-pro focuses on prompt adherence, visual quality, and image detail. After describing the subject, you can further specify the scene, materials, lighting, camera distance, and overall style, turning a passage of text into a clear visual brief. It is well suited for adjusting composition and atmosphere around the same idea, gradually selecting images that better match the goal.
You can create new images from text or submit an existing image link and initiate edits with text instructions. This means the workflow does not have to start from a blank canvas every time: first generate a directional draft, then request changes around the selected image. If the task emphasizes precise local modifications and overall consistency, you can further consider the Kontext series.
Square, portrait, and landscape sizes make it easy to prepare visual drafts for different layouts, and image ratios can also be used to express composition requirements. Generation tasks support a specified quantity, making it suitable for preparing multiple candidate options at once; combined with asynchronous queries or completion callbacks, image tasks can be integrated into a content production backend without keeping the user interface waiting.
Enter the campaign theme, core subject, brand color palette, and desired atmosphere to generate candidate images for advertising backgrounds or promotional visuals. Landscape formats are suitable for exploring key visual layouts, while portrait formats work well for content covers. Deliverables can serve as design communication drafts, after which designers can add official copy, logos, and typography, rather than directly replacing complete ad production.
Generate scene drafts around product appearance descriptions, placement methods, background materials, and lighting to compare studio-style, lifestyle, or artistic expressions. Existing images can also be used as editing inputs. When actual products are involved, compare the results item by item with the real appearance before deciding which images are suitable for subsequent production.
Turn character settings, environmental relationships, color schemes, and artistic direction into prompts to generate illustration or scene concept candidates. Explore different expressions of the same subject by changing the perspective, lighting, and style descriptions. The final deliverable can be a set of direction images for illustrators or art teams to select and refine further, rather than requiring all details to be completed at once.
If the goal is to prepare visual assets for a formal project and you care about prompt expression, details, and image quality, flux-pro is worth considering. flux-dev is better suited for development testing and early-stage concept exploration. FLUX.1 [pro] and FLUX1.1 [pro] are different native versions; when calling flux-pro, its name should not be arbitrarily rewritten as 1.1, nor should specific acceleration effects be assumed based on this.
If starting from a text concept and needing multiple composition candidates, use flux-pro; if the core task is context-aware modification of existing images, it is more suitable to compare flux-kontext-pro or flux-kontext-max. When considering the Flux 2 series, also note the difference in size notation: these endpoints use image aspect ratios and cannot directly copy flux-pro's pixel size settings.
For text-to-image, specify the subject, materials, lighting, and canvas format; for modifying existing images, prepare image_url and clearly describe what to change and preserve.
Submit model=flux-pro, action=generate, prompt, and size=1024x1024 to /flux/images; when editing images, choose edit and provide the image URL, while count is only used for generation.
Save the returned image_url; for asynchronous requests, query via task_id or configure callback_url. Compare key elements before and after modification, then use the generated images in subsequent design work.
A frosted glass perfume bottle placed on a dark stone pedestal, with soft light from the left illuminating the bottle, a simple background, emphasizing glass, stone, and shadows, with no logo text added.
Zoom in to inspect the materials, bottle perspective, and reflections; when you need to continuously preserve details around the original image, compare the specialized Kontext editing model.
When calling it, use the exact model ID flux-pro; do not rewrite it as FLUX1.1 [pro]. FLUX.1 [pro] and FLUX1.1 [pro] are different versions; when choosing this option, evaluate it based on image quality, prompt adherence, and actual task results rather than assuming 1.1 speed performance.
Yes. Use action=edit, and provide image_url, the modification instruction prompt, and size. Edit tasks do not use count to control the quantity. If you want more targeted, context-aware modifications based on an existing image, it is recommended to also compare flux-kontext-pro or flux-kontext-max.
You can use 1024x1024, 1024x1792, or 1792x1024, or specify an image aspect ratio. First choose a square, landscape, or portrait format based on the final layout, then describe the subject position and whitespace requirements in the prompt. When using Flux 2 or Kontext, use their corresponding aspect-ratio formats instead.
In a generate task, specify the number of images with count; one image is generated by default. The returned data list provides links for each image. This is suitable for keeping the main description unchanged, comparing multiple candidates first, and then adjusting the prompt to continue exploring. count does not apply to edit and does not mean every result will be exactly the same.
Submit the model, operation, prompt, and size to POST /flux/images. You can set async=true, then query the task result after obtaining task_id; you can also use callback_url to receive completion notifications. After completion, read image_url from data, then pass it to asset management, review, or design workflows for processing.
Choose a development approach or application suited to this model and follow its setup guide.
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