WAN V2.6 IMAGE TO IMAGE

Wan v2.6 Image to Image is an advanced image-text-to-image model that specializes in image editing and compositional image generation using multiple reference images and detailed text prompts. The model enables users to blend, recompose, and edit scenes by referencing up to three images, with instructions provided in a flexible text prompt. Its interface is designed to support both commercial and partner use cases and is accessible via API or through an interactive playground.

Core functionality centers around “image-to-image” transformations where users supply 1-3 image URLs, accompanied by a text prompt that specifies exactly how these images should be incorporated or modified in the resulting output. For example, the prompt might direct the model to place a character from the first image into the environment of a second image, with additional objects or lighting from a third image, all described in rich, creative language. The relative order of images matters, as the prompt should refer to the reference images by their ordinal numbers: 'image 1', 'image 2', and 'image 3'.

The model accepts images in common formats—JPEG, JPG, PNG (excluding those with alpha channels), BMP, and WEBP—with each required to be between 384 and 5000 pixels on each dimension and no larger than 10MB. Users can provide images by drag-and-drop, URL, or direct upload.

Output images can be finely controlled in size and shape. Users can select from standard aspect ratio presets (such as square_hd, portrait_4_3, landscape_16_9, and others) or specify custom dimensions, as long as total resolution stays within documented bounds (minimum 768x768 to maximum 1280x1280 pixels). The model supports generating between 1 and 4 images per request, offering flexibility for iterative design and comparison.

Additional features include optional prompt expansion using a large language model (LLM) for more effective interpretation and generation from simple prompts. Enabling this can improve quality, but adds three to four seconds to processing time. Safety considerations are built in: the model provides toggles to activate content moderation (safety checker) on both inputs and outputs. Negative prompts are supported, allowing users to guide the model away from unwanted characteristics or content in the generated image (e.g., avoiding low-quality renderings or specific artifacts).

The text prompt system supports both Chinese and English text, with a maximum prompt length of 2000 characters. Users also have access to additional JSON-based configuration, allowing precise control over all model parameters for advanced usage and automation.

The output consists of a high-quality generated image returned as a PNG file accessible via URL, accompanied by a JSON summary including the seed value and metadata. There is also a preview function for immediate review within the user interface. Example results—including composited fantasy scenes—demonstrate the model's capability for detailed, stylistic, and contextually rich image edits.

Ideal for creative professionals, artists, illustrators, and designers who require complex image mashups, custom scene generation, and flexible integration of visual elements, Wan v2.6 Image to Image delivers precision, customization, and efficiency. It particularly shines in scenarios where visual storytelling and intricate recomposition are paramount.

Limitations and best practices include adhering to image resolution and file size guidelines, ensuring correct order of images for accurate prompt interpretation, and adjusting prompt complexity or negative prompts for desired creative direction. Processing time may be modestly increased when using prompt expansion. The model's content moderation can be disabled, allowing for unfiltered outputs when appropriate, but defaults to on for safety.

In summary, Wan v2.6 Image to Image is a versatile and highly configurable tool for unified visual editing, seamlessly merging the best aspects of textual and visual creative instruction.