Seedream v4 Edit
Open and Advanced Large-Scale Image Generative Models.
What it does
Seedream v4 Edit, in practice.
Seedream 4 is a powerful, efficient, and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image composition within a single, integrated framework. Engineered for scalability and efficiency, the model introduces a novel diffusion transformer (DiT) architecture combined with a powerful Variational Autoencoder (VAE). This design enables the fast generation of native high-resolution images up to 4K, while significantly reducing computational requirements compared to its predecessors. The primary goal of Seedream 4 is to extend traditional T2I systems into a more interactive and multidimensional creative tool. It is designed
- Unified Multimodal Architecture: It integrates T2I generation, image editing, and multi-image composition into a single model, allowing for seamless transitions between different creative workflows.
- Efficient and Scalable Design: The model features a highly efficient DiT backbone and a high-compression VAE, achieving over 10x inference acceleration compared to Seedream 3.0 while delivering superior performance. This architecture is hardware-friendly and easily scalable.
- Ultra-Fast, High-Resolution Output: Seedream 4 can generate native high-resolution images (from 1K to 4K) in as little as 1.4 to 1.8 seconds for a 2K image, greatly enhancing user interaction and production efficiency.
- Advanced Multimodal Capabilities: The model excels at complex tasks such as precise, instruction-based image editing, in-context reasoning, and generating new images by blending elements from multiple reference images.
- Professional and Knowledge-Based Content Generation: Beyond artistic imagery, Seedream 4 can generate structured and knowledge-based content, including charts, mathematical formulas, and professional design materials, bridging the gap between creative expression and practical application.
- Advanced Training and Acceleration: The model is pre-trained on billions of text-image pairs and utilizes a multi-stage post-training process (CT, SFT, RLHF) to enhance its capabilities. Inference is accelerated through a combination of adversarial distillation, quantization, and speculative decoding.
Product photo workspace
This page is a model reference. The workspace supports white backgrounds, scene changes, packaging text edits and model try-on using Qwen Image Edit.
Parameters
What you can set.
| Parameter | What it does | Options |
|---|---|---|
images | The image to edit, can be a URL or base64 encoded image. | |
prompt | The editing instruction describing the desired changes to the image. | |
size | The size of the generated media in pixels (width*height). | default 2048*2048 |
Sample prompt
The prompt behind the sample.
Turn this photo into a clay-style image. Place it in a Polaroid photo.
size: 2048*2048enable_sync_mode: enable_base64_output: FAQ
Short answers.
How much does Seedream v4 Edit cost?
List price starts at $0.041 per image at the base resolution; higher resolutions and longer durations cost more. Per-use pricing, no subscription. Model prices are reference prices. The prompt workspace is free during the period shown on the homepage; no automatic charges.
Is Seedream v4 Edit good for e-commerce product photos?
It is an image-editing model, which is the core job here: background cleanup, relighting, inpainting, label or packaging text fixes and upscaling. Keep one instruction per pass so the product, logo and SKU details stay locked. ByteDance's standard content policy applies.
What does Seedream v4 Edit take as input?
It is a image editing model. Open and Advanced Large-Scale Image Generative Models.
How do I use Seedream v4 Edit?
Upload the image and describe the edit narrowly. Inpainting, restyle, upscale and background work all do better with one instruction per pass than with a paragraph of changes. Register or sign in to edit product photos with Qwen Image Edit. Other models on this page are catalog references.
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