Seedream v4 Edit API by ByteDance
Open and Advanced Large-Scale Image Generative Models.
Seedream 4.0: el modelo unificado de creación visual de ByteDance
NUEVO LANZAMIENTOEl motor de creación de imágenes de última generación de Doubao
Seedream 4.0 es el modelo de creación de imágenes de última generación de ByteDance, concebido como una herramienta profesional que unifica generación y edición. Un mismo modelo gestiona la generación de imágenes a partir de texto, la edición de imágenes y la generación con múltiples imágenes, haciendo que tu proceso creativo, de la inspiración a la realización, sea más eficiente y controlable.
Aspectos destacados del modelo
Con cinco capacidades fundamentales: Edición de Instrucciones Precisas, Alta Preservación de Características, Comprensión Profunda de la Intención, Entrada/Salida de Múltiples Imágenes y Resolución Ultra HD. Abarca escenarios creativos diversos, dando vida a cada inspiración al instante con alta calidad.
Edición de Instrucciones Precisas
Simplemente describe tus necesidades en lenguaje sencillo para ejecutar con precisión operaciones de añadir, eliminar, modificar y reemplazar. Permite aplicaciones en diseño comercial, creación artística y entretenimiento.
Alta Preservación de Características
Comprensión Profunda de la Intención
Entrada/Salida de Múltiples Imágenes
Introduce múltiples imágenes a la vez, admitiendo operaciones de edición complejas como combinación, migración, reemplazo y derivación, logrando síntesis de alta dificultad
Resolución Ultra HD
Resolución mejorada de nuevo, con salida en ultra alta definición para una calidad de imagen de nivel profesional
Casos de uso
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 Principales
Capacidades avanzadas de comprensión de texto y generación de imágenes, compatible con diversos estilos artísticos y requisitos profesionales, del concepto a la obra final en un solo paso.
Comandos de edición basados en lenguaje natural, compatibles con adición/eliminación de objetos, transferencia de estilos, reemplazo de fondos y operaciones de edición más complejas.
Capacidad revolucionaria de entrada de múltiples imágenes que permite síntesis de imágenes complejas, migración de estilos y combinaciones creativas con un control sin precedentes.
¿Por qué elegir Seedream 4.0?
Solución Todo en Uno
Un único modelo gestiona la generación, edición y composición: sin necesidad de cambiar entre diferentes herramientasCalidad Profesional
Calidad de salida a nivel comercial con control preciso sobre cada detalleEstilo Coherente
Mantiene la coherencia del personaje y el estilo a lo largo de múltiples generaciones y edicionesEspecificaciones Técnicas
Descubre todo el potencial de Seedream 4.0
Únete a creadores de todo el mundo que están revolucionando la creación de contenido visual con el modelo de IA de imagen integrado más avanzado de 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. |
