How do credits work for Wan v2.6, and how does pricing compare to other image editing models?

Wan v2.6 uses JAI Portal's pay-as-you-go credit system, charging per generation based on resolution and number of outputs. A typical square_hd single image costs around 15-20 credits, while generating four images at once scales proportionally. This is competitive with models like <a href="/model/qwen-image-2-edit">Qwen Image 2 Edit</a> and <a href="/model/nano-banana-2-pro-edit">Nano Banana 2 Pro Edit</a>, which charge similar rates for comparable resolutions. Wan v2.6's unique multi-image composition justifies slightly higher credit use compared to single-image editors. You only pay for successful generations, and there are no subscription fees—ideal for project-based work or occasional creative tasks.

Wan v2.6 Image to Image

Combine elements from up to 3 images with text instructions in Chinese or English.

"Place the wizard from image 2 in the ancient library from image 3, holding and studying the magical crystal orb from image 1. The orb's glow illuminates his face with purple and blue light. Floating candles around him, ancient books visible in the background. Mystical, dramatic lighting, fantasy art style, highly detailed.."

Image 1

Image 2

Image 3

Generated Result

Generated

Upload your image and transform it in seconds

12,000+ images created this month

📄 About Wan v2.6 Image to Image

Wan v2.6 Image to Image is an advanced AI-powered image generation model designed to revolutionize creative workflows by merging and transforming up to three reference images into a single, cohesive visual output. By harnessing state-of-the-art image-to-image technology, this model allows users to input multiple images and describe, in natural language, how elements from each should be combined, manipulated, or enhanced within the final image. Whether you’re looking to place a character from one photo into the environment of another, or merge objects, textures, and backgrounds from several sources, Wan v2.6 delivers highly detailed, imaginative results with remarkable realism. The model stands out for its robust multi-image composition capabilities, supporting both English and Chinese instructions. Users can control not only what appears in the final output but also what should be excluded, thanks to a negative prompt feature. Flexible image size options (including custom dimensions and popular aspect ratios) enable tailored outputs for a variety of creative and professional needs. The model also supports the generation of up to four images per prompt, providing multiple variations for every project. Integrated prompt expansion leverages large language models (LLMs) to optimize and enhance user instructions, ensuring that even complex or nuanced requests are interpreted accurately and rendered with precision. For those requiring reproducibility, a random seed parameter is available, and content safety is prioritized via an optional moderation system. Wan v2.6 Image to Image is perfect for graphic designers, illustrators, marketers, and content creators seeking to quickly produce composite visuals, concept art, marketing assets, or enhanced product photos. Its intuitive workflow lets you reference multiple source images—such as characters, objects, or environments—and direct the AI using descriptive prompts like, “Place the wizard from image 2 in the ancient library from image 3, holding the magical orb from image 1.” The model then synthesizes these instructions to generate high-quality images in seconds. Ideal use cases range from visual storytelling and fantasy art to branded social media content, advertising visuals, and educational illustrations. The bilingual prompt support makes Wan v2.6 accessible to a global audience, while the pay-as-you-go credit system ensures flexibility and scalability for any project size. With its blend of creative control, versatility, and cutting-edge AI technology, Wan v2.6 Image to Image empowers users to push the boundaries of digital image generation and composition.

✨ Key Features

Multi-image composition: Combine elements from up to three reference images into a single, unified visual output.

Natural language control: Use English or Chinese prompts to direct the composition, placement, and appearance of elements.

Negative prompt support: Specify content or styles to avoid, helping ensure precise, high-quality results.

Flexible image sizes: Choose from custom dimensions or popular aspect ratios, including square, portrait, and landscape formats.

Prompt expansion: Enable LLM-powered optimization to interpret and enhance user instructions for more accurate results.

Multiple outputs: Generate up to four image variations per prompt for creative exploration.

Built-in safety checker: Optional content moderation ensures compliance with quality and safety standards.

💡 Use Cases

⚡Creating fantasy or sci-fi concept art by merging characters and environments from different images.

⚡Producing marketing visuals by integrating products into branded backgrounds or lifestyle scenes.

⚡Generating unique social media content by combining personal photos with artistic elements.

⚡Developing educational illustrations by placing objects or people into new contexts.

⚡Designing book covers, posters, or album art with seamless visual compositions.

⚡Rapid prototyping for game or animation storyboards.

⚡Enhancing product photos by adding or removing elements based on descriptive prompts.

🎯 Best For

🎯 Graphic designers, illustrators, content creators, and marketers seeking advanced multi-image AI composition.

👍 Pros

✓Supports up to three reference images for complex, layered compositions.

✓Accepts detailed natural language prompts in both English and Chinese.

✓Customizable image size and aspect ratio options cater to diverse project needs.

✓Prompt expansion leverages LLMs for improved prompt interpretation and output quality.

✓Fast processing delivers high-quality images in seconds.

✓Optional safety checker helps maintain content appropriateness.

⚠️ Considerations

△Requires high-quality reference images for best results.

△Limited to a maximum of three input images per generation.

△Processing times may slightly increase when using prompt expansion.

△Outputs are influenced by the clarity and detail of user prompts.

📚 How to Use Wan v2.6 Image to Image

Upload 1 to 3 reference images (each between 384-5000px, max 10MB).

Write a detailed prompt describing how elements from the reference images should be combined or used in the final image.

Optionally add a negative prompt to specify elements or qualities to avoid.

Select your desired image size and aspect ratio from the available options.

Choose the number of images to generate (up to four) and enable prompt expansion if desired.

Submit your request and review the AI-generated images for download or further iteration.

💡 Pro Tips for Wan v2.6 Image to Image

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Reference Images Clearly in Your Prompt Always use 'image 1', 'image 2', and 'image 3' in your prompt to tell the model exactly which elements to pull from each reference. For example, 'Place the character from image 2 into the forest from image 1' ensures the AI knows which source to use for each component. This explicit referencing dramatically improves composition accuracy and reduces unwanted blending.

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Upload High-Quality Reference Images Use sharp, well-lit reference images between 384-5000px for best results. Blurry or low-resolution sources will degrade the final output. Ensure your subjects are clearly visible with good contrast. If you need to enhance image quality first, consider using Qwen Image 2 Pro Edit to upscale or refine your references before combining them in Wan v2.6.

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Enable Prompt Expansion for Complex Compositions When combining three images with detailed instructions, turn on prompt expansion to let the LLM optimize your request. This adds 3-4 seconds to processing but significantly improves how the model interprets layered instructions like lighting, perspective, and element placement. For simpler two-image blends, you can skip expansion to save time and credits.

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Use Negative Prompts to Avoid Common Issues Add terms like 'distorted faces', 'unnatural lighting', 'blurry edges', or 'mismatched perspective' to your negative prompt. This helps the model avoid typical multi-image composition artifacts. If you need more control over specific edits rather than full composition, try FLUX 2 Dev Edit for precise inpainting and masking workflows.

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Generate Multiple Variations for Best Results Set num_images to 3 or 4 to produce several variations in one run. Multi-image composition can yield different interpretations of your prompt, so generating multiple outputs lets you pick the best blend. This approach is more credit-efficient than running separate single-image generations and gives you creative options to compare side-by-side.

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Match Aspect Ratios to Your Final Use Case Choose portrait_16_9 for social media stories, landscape_16_9 for YouTube thumbnails, or square_hd for Instagram posts. Selecting the right aspect ratio from the start saves you from cropping or resizing later. For custom dimensions beyond the presets, use the 'custom' option to specify exact width and height between 1024-4096px for specialized print or web layouts.

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Frequently Asked Questions

You can use between one and three reference images for each generation. Simply upload your chosen images, and refer to them as 'image 1', 'image 2', or 'image 3' within your prompt for clear instructions.

Yes, Wan v2.6 Image to Image fully supports prompts in both Chinese and English. This allows a wide range of users to interact with the model using their preferred language.

Prompt expansion uses a large language model to optimize and clarify your instructions, helping the AI better understand complex or nuanced requests. This typically results in more accurate and detailed image outputs.

Pricing varies by model and is based on a pay-as-you-go credit system. You only pay for what you use, making it flexible for both small and large projects.

Yes, there is an optional safety checker that reviews generated content to help maintain quality and prevent inappropriate results. Users can enable or disable this feature as needed.

Wan v2.6 uses JAI Portal's pay-as-you-go credit system, charging per generation based on resolution and number of outputs. A typical square_hd single image costs around 15-20 credits, while generating four images at once scales proportionally. This is competitive with models like Qwen Image 2 Edit and Nano Banana 2 Pro Edit, which charge similar rates for comparable resolutions. Wan v2.6's unique multi-image composition justifies slightly higher credit use compared to single-image editors. You only pay for successful generations, and there are no subscription fees—ideal for project-based work or occasional creative tasks.

Yes, all images generated on JAI Portal with paid credits come with full commercial-use rights. You can use Wan v2.6 outputs in advertising, social media, print materials, product packaging, and client deliverables without additional licensing fees. This applies whether you're a freelancer, agency, or in-house creative team. Just ensure your reference images are either your own original content or properly licensed for commercial use, as the model combines elements from your uploads. For brand-safe headshots or portraits, consider AI Headshot Generator or FLUX 2 Face to Full Portrait for controlled, professional outputs.

Wan v2.6 accepts common image formats including JPEG, PNG, and WebP for reference uploads. Each input image must be between 384-5000px on the longest side and under 10MB. Output images are delivered as high-quality WebP files at resolutions ranging from 1024x1024 (square) up to 4096px on the longest dimension for custom sizes. The model automatically handles format conversion, so you don't need to preprocess your uploads. For projects requiring specific output formats like PNG or TIFF, you can convert the WebP results using standard image tools after download. If you need higher resolutions beyond 4096px, consider upscaling the output with a dedicated model post-generation.

Wan v2.6 is optimized for photographic and illustrative content rather than precise text rendering. While it can preserve some visible text or logos from reference images, the model may distort or blur fine typography during composition. If your project requires sharp, legible text overlays or logo integration, it's better to add those elements in post-production using graphic design software. For image editing tasks that prioritize text accuracy, OpenAI GPT Image 2 Edit offers better text handling. Wan v2.6 excels at blending subjects, backgrounds, and objects—use it for the visual composition, then layer text separately for professional results.

Use the seed parameter to lock in a specific random seed value (0-2147483647) for reproducible results. When you generate an image you like, note the seed used and reapply it in future runs with identical prompts and settings. This ensures the model produces the same composition and details. Keep in mind that changing any input—prompt wording, reference images, image size, or negative prompt—will alter the output even with the same seed. For iterative workflows where you want to tweak one element while keeping others constant, save your seed and adjust only the parameter you're testing. This technique is especially useful for A/B testing different prompts or refining specific details across multiple generations.

⚖️ How Wan v2.6 Image to Image Compares

Wan v2.6 Image to Image stands out on JAI Portal for its ability to combine up to three reference images in a single generation, making it ideal for complex visual compositions that require merging characters, objects, and backgrounds from multiple sources. Unlike single-image editors like FLUX 2 Dev Edit or Qwen Image 2 Edit, which excel at localized edits and inpainting on one image, Wan v2.6 specializes in multi-image synthesis driven by natural language prompts in both English and Chinese. If you need to place a subject from one photo into an environment from another while adding objects from a third, Wan v2.6 is your best choice. For simpler edits—like removing backgrounds, changing colors, or refining details on a single image—Qwen Image 2 Pro Edit or Nano Banana 2 Pro Edit offer faster, more credit-efficient workflows. Wan v2.6's bilingual support and prompt expansion make it accessible to global users and capable of handling nuanced, multi-layered instructions. Choose Wan v2.6 when your project demands creative composition across multiple source images, and opt for single-image editors when precision edits on one photo are sufficient. Explore side-by-side comparisons and test different models at jaiportal.com to find the perfect fit for your workflow.