Introducing WaveSpeedAI Qwen Image Layered on WaveSpeedAI

Introducing Qwen-Image Layered: Revolutionary AI-Powered Layer Decomposition for Image Compositing

The way we edit images is about to change forever. WaveSpeedAI is excited to announce the availability of Qwen-Image Layered, a groundbreaking AI model that automatically decomposes any image into multiple clean RGBA layers—bringing Photoshop-level layer editing capabilities to a simple API call.

Developed by Alibaba’s Qwen AI team and released in December 2025, this model represents a significant leap forward in image editing technology. What once required 30-60 minutes of painstaking manual masking in traditional software can now be accomplished in seconds with intelligent, semantically-aware layer separation.

What is Qwen-Image Layered?

Qwen-Image Layered is a unified image-layer decomposition model that transforms a single flat image into multiple independent RGBA layers, each with clean alpha transparency. Unlike traditional background removal tools that simply separate foreground from background, this model intelligently identifies and isolates multiple semantic elements within an image—people, objects, backgrounds, and even partially occluded regions.

The model is built on an end-to-end diffusion architecture featuring three key innovations:

• RGBA-VAE: A specialized variational autoencoder that unifies the latent representations of RGB and RGBA images
• VLD-MMDiT: Variable Layers Decomposition architecture capable of handling any number of output layers
• Multi-stage Training: Trained on high-quality multilayer images extracted from professional PSD files

What truly sets this model apart is its ability to reconstruct hidden regions. When a person stands in front of a building, traditional segmentation tools simply cut around the person. Qwen-Image Layered goes further—it intelligently fills in the background areas that were previously obscured, giving you complete, usable layers ready for compositing.

Key Features

• Controllable Layer Count: Specify exactly how many RGBA layers you want (1-8+), tailoring output to your specific workflow needs
• Clean RGBA Outputs: Each layer includes proper alpha transparency for seamless compositing and editing
• Prompt-Guided Separation: Add optional text descriptions to improve semantic grouping in complex scenes
• Recursive Decomposition: Any layer can be further decomposed, enabling infinite levels of detail
• Occlusion Handling: Automatically reconstructs content hidden behind foreground elements
• Soft Edge Quality: Produces natural-looking alpha channels with smooth transitions

Real-World Use Cases

Creative Design & Marketing

Transform product photography into flexible assets. Extract a product, its shadow, and background into separate layers for rapid iteration on marketing materials, social media posts, and advertisements. Design teams can create dozens of variations from a single source image without reshooting.

E-commerce & Product Photography

Isolate products from studio backgrounds, then composite them onto lifestyle scenes, seasonal themes, or branded backdrops. With clean alpha channels, edges remain crisp and professional without the halos that plague automated tools.

Video Production & VFX

Prepare static elements for motion graphics and video compositing. Extract subjects, props, and environmental elements into layer stacks that import directly into After Effects, DaVinci Resolve, or other compositing software.

Game Development & Asset Creation

Generate game-ready assets from reference images. Decompose concept art or photographs into reusable sprite layers with proper transparency for 2D game development or UI design.

Social Media Content Creation

Create eye-catching social content with layer-based effects. Separate subjects from backgrounds to add depth blur, color grading to specific elements, or swap environments entirely—all from a single upload.

Architectural Visualization

Extract building elements, landscaping, and sky into separate layers for presentation materials. Quickly swap sky conditions, adjust lighting atmospheres, or composite buildings into different environmental contexts.

Getting Started with WaveSpeedAI

Using Qwen-Image Layered on WaveSpeedAI is straightforward:

1. Upload your source image or provide a public URL
2. Set your layer count using the num_layers parameter (e.g., 4 for a balanced decomposition)
3. Add an optional prompt to guide semantic separation (e.g., “a person standing in front of a building”)
4. Run the model and receive your RGBA layers
5. Download and composite the layers in your preferred editing software

API Integration

WaveSpeedAI provides a ready-to-use REST API with:

• No cold starts: Models are always warm and ready
• Fast response times: Get your layers in seconds, not minutes
• Affordable pricing: Starting at just $0.05 per layer

Pricing Structure

Layers	Price
1	$0.05
2	$0.10
3	$0.15
4	$0.20
5	$0.25
8	$0.40

Best Practices for Optimal Results

To get the most from Qwen-Image Layered:

• Use clear subjects: Images with well-defined subjects and good foreground/background separation yield the best results
• Ensure good lighting: Properly lit images with minimal motion blur decompose more cleanly
• Start with fewer layers: For simple scenes, 3-4 layers often suffice; increase layer count for complex compositions
• Leverage prompts: When subjects are ambiguous or overlapping, add descriptive prompts to guide layer grouping
• Consider iterative decomposition: For highly complex images, decompose broadly first, then recursively decompose individual layers for finer control

Known Considerations

While remarkably capable, the model performs best with:

• Clear subject-background separation
• Limited heavy occlusion between subjects
• Moderate scene complexity

Highly intertwined subjects (like people hugging) may show some bleed between layers, and extremely fine details like individual hair strands may require touch-up in post-processing.

Why Choose WaveSpeedAI?

WaveSpeedAI eliminates the infrastructure headaches of running AI models. Our platform offers:

• Instant availability: No GPU provisioning or container spin-up delays
• Scalable inference: Handle one request or thousands with consistent performance
• Simple integration: Clean REST APIs with comprehensive documentation
• Cost efficiency: Pay only for what you use with transparent, predictable pricing

Conclusion

Qwen-Image Layered represents a paradigm shift in image editing workflows. By automating the tedious process of layer separation with intelligent, semantically-aware decomposition, it empowers creators to focus on what matters: bringing their creative visions to life.

Whether you’re a solo content creator looking to speed up your workflow, or an enterprise team processing thousands of images daily, Qwen-Image Layered on WaveSpeedAI provides the speed, quality, and affordability you need.

Ready to transform your image editing workflow? Try Qwen-Image Layered on WaveSpeedAI today and experience the future of layer-based image editing.

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