Seedream 4.5 Image to Image Editing

About this model

Seedream 4.5 is a strong fit for text-to-image and image-to-image work when you need more cinematic visuals, better consistency across related images, stronger in-image text, and support for 2K, 4K, or custom output sizes.

When is this model useful?

Seedream 4.5 is the better choice when you need more than a quick draft. It is built for outputs that feel more production-ready, with cleaner composition, more readable text in the scene, and more stable related image sets.

Best fit tasks

Text-to-image generation for ad creatives, posters, hero sections, packaging, presentations, and branded key visuals.
Creating a related series of images where a character, product, or overall visual style should stay more stable across multiple results.
Image-to-image edits for photos, illustrations, interiors, and product scenes when you want to change lighting, materials, mood, background, or composition without rebuilding the image manually.
Work that includes visible text, scene structure, or spatial logic such as packaging, banners, signs, interfaces, and educational or technical visuals.
Multi-reference workflows where the final image needs to combine features from several source images into one coherent result.

Main advantages

The model is geared toward more polished outputs, with cinematic lighting, cleaner materials, stronger rendering, and a more professional visual finish.
It keeps related results more stable than lighter models, which makes it useful for campaigns, banner sets, character variations, and branded visual systems.
It supports 2K, 4K, and custom width and height, so you can match the output more closely to a banner, slide, marketplace image, catalog, or print layout.
It is stronger than basic generators on visible text, scene logic, proportions, and object placement.
It works for both text-to-image and image-to-image, including multi-reference workflows with 1 to 14 input images.

Limitations to know

It creates still images, not video, animation, or an editable layered design file.
In AISVIT, this model does not include a layer-based editor or mask controls, so very precise local edits often require a few prompt-and-reference iterations.
Sequential image generation runs in auto mode, so the model decides how to form the related set. It is not a rigid storyboard system with guaranteed frame-to-frame identity.
Tiny text, complex typography, hands, micro-details, and very dense scenes can still require multiple attempts.
Results improve a lot when the prompt and references are specific. Vague requests tend to produce more generic styling.

How to use this model

The easiest workflow is to describe the goal first, choose the output size second, and add references or series mode only when they genuinely help the task.

Simple workflow

Write the prompt in plain language: what should be in the image, what style and lighting you want, the camera angle, mood, what details should stay, and what text should appear in the image if any.
Choose Size. 2K works well for most everyday tasks and faster iteration, while 4K is better when you need more detail for presentations, larger creatives, or tighter cropping.
If you need an exact layout size, choose custom and set Width and Height. In simple terms, this is a manual way to choose the image width and height in pixels.
If size is not custom, choose Aspect ratio: 1:1 for square outputs, 16:9 for banners and landing pages, 9:16 for stories and vertical ads, or match input image when you want to follow the source image proportions.
For image-to-image work, upload one or more reference images and say clearly what should stay unchanged and what should be modified. That gives the model clearer editing boundaries.

Supported inputs

Required: a text prompt.
Optional: 1 to 14 reference images for image-to-image, multi-reference generation, and example-guided editing.
In the AISVIT upload flow, JPG, PNG, and WEBP are the safest image formats to use.
For controlled editing, clearer source images with less compression and less visual noise usually work better.

What you get

One generated image or a related image set if series mode is enabled.
2K, 4K, or custom width and height output within the 1024-4096 px range for both dimensions.
Supported frame shapes: match input image, 1:1, 4:3, 3:4, 16:9, 9:16, 3:2, 2:3, and 21:9.
A finished raster image file returned by the provider. In AISVIT, this model does not expose a separate manual PNG versus JPEG selector.