Customize your input with more control.
Customize your input with more control.
Hint: Drag and drop image files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL. Accepted file types: jpg, jpeg, png, webp, gif, avif, heic, heif
Hint: Drag and drop image files from your computer, images from web pages, paste from clipboard (Ctrl/Cmd+V), or provide a URL. Accepted file types: jpg, jpeg, png, webp, gif, avif, heic, heif
Customize your input with more control.
Your request will cost $0.075 per generation.
FASHN's Virtual Try-On V1.5 delivers precise garment rendering at 576x864 resolution for $0.075 per generation, accurately preserving text, patterns, and fabric details from both on-model and flat-lay reference photos. Trading raw speed for photographic accuracy, the model handles three garment categories (tops, bottoms, one-pieces) with automatic detection and three quality modes to balance performance needs. Built for e-commerce teams running high-volume product visualization where garment detail accuracy directly impacts conversion rates.
Use Cases: E-commerce Product Visualization | Fashion Catalog Generation | Virtual Fitting Room Applications
At $0.075 per generation, FASHN V1.5 positions as a specialized virtual try-on solution with configurable quality modes.
| Metric | Result | Context |
|---|---|---|
| Resolution | 576x864 | Fixed output dimensions optimized for full-body garment visualization |
| Cost per Generation | $0.075 | 13 generations per $1.00 on fal |
| Quality Modes | 3 options | Performance/Balanced/Quality trade speed for rendering accuracy |
| Batch Processing | 1-4 samples | Generate multiple variations per request to increase success rate |
| Related Endpoints | FASHN V1.6 | Newer version with enhanced capabilities at same pricing tier |
FASHN V1.5 uses a dual-input architecture requiring both model and garment images, with intelligent preprocessing that adapts to flat-lay product photos or on-model references. Unlike general image-to-image models, this approach preserves garment-specific details like logos, text, and pattern alignment while maintaining realistic fabric draping and body proportions.
What this means for you:
Automatic Garment Detection: Category auto-detection handles tops, bottoms, and one-pieces without manual classification, reducing workflow friction for catalog-scale operations
Flexible Source Images: Accepts both flat-lay product photography and on-model references via garment_photo_type parameter, eliminating need for specialized photo shoots
Quality-Speed Control: Three rendering modes (performance/balanced/quality) let you optimize for preview speed during creative iteration or final output quality for production assets
Batch Variation Generation: 1-4 sample outputs per request with optional seed control increases chances of ideal results without sequential API calls
| Spec | Details |
|---|---|
| Architecture | FASHN Virtual Try-On V1.5 |
| Input Formats | Model image (URL/base64), Garment image (URL/base64) |
| Output Formats | PNG (highest quality), JPEG (faster processing) |
| Output Resolution | 576x864 pixels |
| License | Commercial use permitted |
API Documentation | Quickstart Guide | Enterprise Pricing
FASHN Virtual Try-On V1.6 – FASHN V1.5 ($0.075) offers proven stability for production workflows, while V1.6 ($0.075) introduces enhanced rendering capabilities at the same price point. V1.6 represents the latest iteration with improved detail preservation for teams prioritizing cutting-edge accuracy over established stability.
Bytedance Image to Image – FASHN V1.5 specializes in garment-specific virtual try-on with automatic category detection and fabric detail preservation. Bytedance's general image editing approach offers broader transformation capabilities for teams needing multi-purpose image manipulation beyond fashion use cases.
