Seedream v4 Edit Sequential API by ByteDance
Open and Advanced Large-Scale Image Generative Models.
Seedream 4.0 - Modelo de Criação Visual Tudo-em-Um da ByteDance
NOVOA Mais Recente Geração do Motor de Criação de Imagens da Doubao
O Seedream 4.0 é o modelo de criação de imagens de última geração da ByteDance, posicionado como uma ferramenta profissional de "geração e edição integradas". Um mesmo modelo é capaz de lidar com tarefas de texto para imagem, edição de imagens e geração com múltiplas imagens, tornando sua jornada criativa, da inspiração à concretização, mais eficiente e controlável.
Destaques do Modelo
Com cinco capacidades principais: Edição por Instrução de Precisão, Alta Preservação de Características, Compreensão Profunda da Intenção, Entrada/Saída de Múltiplas Imagens e Resolução Ultra HD. Abrange diversos cenários de criação, dando vida a cada inspiração instantaneamente e com alta qualidade.
Edição por Instrução de Precisão
Basta descrever o que você precisa em linguagem simples para executar com precisão operações de adição, remoção, modificação e substituição. Possibilita aplicações em design comercial, criação artística, entretenimento e outras áreas.
Alta Preservação de Características
Compreensão Profunda de Intenção
Entrada/Saída Multi-Imagem
Insira várias imagens de uma só vez, com suporte a operações de edição complexas como combinação, transferência, substituição e derivação, alcançando composições de alta complexidade
Resolução Ultra HD
Resolução novamente aprimorada, com suporte a saída em ultra alta definição para uma qualidade de imagem de nível profissional
Cenários de Aplicação
Prompt Examples & Creative Templates
Discover the power of Seedream 4.0 with these carefully crafted prompt examples. Each template showcases specific capabilities and helps you achieve professional results.
Perspective & Composition Control
Transform camera angles, adjust scene distance, and modify aspect ratios with precisionChange the camera angle from eye-level to bird's-eye view, adjust the scene from close-up to medium shot, and convert the image aspect ratio to 16:9. Maintain all original elements and lighting while adapting the composition for the new perspective and format.
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Mathematical Whiteboard Creation
Generate clean whiteboard with precise mathematical formulas and equationsCreate a clean white whiteboard with the following mathematical equations written in clear, professional handwriting: E=mc², √(9)=3, and the quadratic formula (-b±√(b²-4ac))/2a. Use black or dark blue marker style, with proper spacing and mathematical notation.
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Sketch to Reality Transformation
Transform rough sketches into detailed realistic objects - bringing wild imagination to lifeBased on this rough sketch, generate a vintage television set from the 1950s-60s era. Transform the abstract lines and shapes into a realistic, detailed old-style TV with wooden cabinet, rounded screen, control knobs, and period-appropriate design elements. Make the vague concept concrete and lifelike.
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Lossless Detail Enhancement
Maximize original image detail retention, avoiding AI-generated artifacts for truly lossless editingEnhance this image while maximizing the preservation of original details. Avoid any AI-generated 'plastic' or 'oily' artifacts. Maintain authentic textures, natural lighting, and original image characteristics. Focus on clean, lossless enhancement that respects the source material's integrity.
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Creative Font Styling
Transform plain text into artistic, creative typography while maintaining readabilityTransform all the text in this image into creative, artistic fonts. Replace the standard typography with stylized lettering that matches the image's aesthetic - use decorative fonts, calligraphy styles, or artistic text treatments. Maintain the same text content and layout while making the typography more visually appealing and creative.
Capacidades Principais
Capacidades avançadas de compreensão de texto e geração de imagens, suportando diversos estilos artísticos e requisitos profissionais, do conceito à obra final em uma única etapa.
Comandos de edição baseados em linguagem natural, com suporte a adição/remoção de objetos, transferência de estilo, substituição de fundo e operações de edição ainda mais complexas.
Capacidade revolucionária de entrada com múltiplas imagens, permitindo composições de imagem complexas, transferência de estilo e combinações criativas com um controle sem precedentes.
Por que Escolher Seedream 4.0?
Solução Tudo-em-Um
Um único modelo lida com geração, edição e composição - sem necessidade de alternar entre diferentes ferramentasQualidade Profissional
Qualidade de saída de nível comercial, com controle preciso sobre cada detalheEstilo Consistente
Mantém a consistência de personagem e de estilo ao longo de várias gerações e ediçõesEspecificações Técnicas
Experimente o Poder do Seedream 4.0
Junte-se a criadores do mundo todo na revolução da criação de conteúdo visual com o mais avançado modelo de IA de imagem integrado da ByteDance.
Seedream 4: A next-generation multimodal image generation system developed by ByteDance Seed
Model Card Overview
| Field | Description |
|---|---|
| Model Name | Seedream 4 |
| Developed by | ByteDance Seed Team |
| Release Date | September 9, 2025 |
| Model Type | Multimodal Image Generation |
| Related Links | Official Website, Technical Report (arXiv), GitHub Organization (ByteDance-Seed) |
Introduction
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 to handle complex tasks involving precise image editing, in-context reasoning, and multi-image referencing, pushing the boundaries of generative AI for both creative and professional applications.
Key Features & Innovations
Seedream 4 introduces several key advancements in image generation technology:
- 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.
Model Architecture & Technical Details
Seedream 4's architecture is a significant leap forward, focusing on efficiency and power. The core components are a diffusion transformer (DiT) and a Variational Autoencoder (VAE).
- Pre-training Data: Billions of text-image pairs, including a specialized pipeline for knowledge-related data like instructional images and formulas.
- Training Strategy: A multi-stage approach, starting at a 512x512 resolution and fine-tuning at higher resolutions up to 4K.
- Post-training: A joint multi-task process involving Continuing Training (CT), Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human Feedback (RLHF) to enhance instruction following and alignment.
- Inference Acceleration: A holistic system combining an adversarial learning framework, hardware-aware quantization (adaptive 4/8-bit), and speculative decoding.
Intended Use & Applications
Seedream 4 is designed for a wide range of creative and professional applications, moving beyond simple image generation to become a comprehensive visual content creation tool.
- Creative Content Generation: Creating high-quality, artistic images, illustrations, and concept art from text prompts.
- Advanced Image Editing: Performing complex edits on existing images using natural language instructions, such as adding or removing objects, changing styles, and modifying backgrounds.
- Design and Marketing: Generating professional design materials, product mockups, and marketing visuals with precise control over text and branding elements.
- Educational and Technical Content: Creating structured, knowledge-based visuals like diagrams, charts, and mathematical formulas for educational or technical documentation.
- Multi-Image Composition: Blending elements from multiple source images to create new compositions, such as virtual try-ons for fashion or combining characters with new scenes.
Performance
Seedream 4 has demonstrated state-of-the-art performance on both internal and public benchmarks as of September 18, often outperforming other leading models in text-to-image and image editing tasks.
MagicBench (Internal Benchmark)
| Task | Performance Summary |
|---|---|
| Text-to-Image | Achieved high scores in prompt following, aesthetics, and text-rendering. |
| Single-Image Editing | Showed a good balance between prompt following and alignment with the source image. |
