Wan 2.7 Image Pro — 4K AI Image Generation

Text-to-Image — Write a prompt and generate a single high-quality image. 4K resolution is available here, with thinking mode enhancing the output for complex prompts. Supports up to 4 outputs per request.

Image Editing — Upload up to 9 source images and describe what you want done. The model can apply style transfer from one image to another, swap characters or objects between images, blend multiple references into a unified composition, or restyle the entire scene based on your instruction. Put the editing instruction in the prompt and pass the source images in the reference field.

Image Set Generation — Enable image set mode to generate up to 12 coherent, related images from a single prompt. This is designed for consistent character sheets, product photography from multiple angles, storyboard sequences, and any workflow where the outputs need to feel like they belong together.

Most image generators process your prompt directly into pixels. Wan 2.7 Image Pro's thinking mode adds a reasoning step before generation begins.

The model analyzes your prompt — working through spatial relationships ("in front of," "behind," "overlapping"), compositional intent (rule of thirds, centered subject, symmetry), multi-element interactions, and stylistic cues — before committing to a generation direction.

This matters most for:

Complex prompts — When you describe more than 2–3 interacting elements, thinking mode helps the model keep track of each and place them correctly.

Spatial precision — "A cat sitting on a red sofa on the left, with a window behind it showing a rainy street" is the kind of instruction that benefits from reasoning before rendering.

Style fidelity — When your prompt references specific artistic styles, periods, or techniques, thinking mode interprets the intent more accurately.

Thinking mode increases generation time slightly but consistently delivers better results for non-trivial prompts. It's enabled by default for text-to-image on NeonLights AI.

The multi-image editing capability is one of Wan 2.7 Image Pro's most distinctive features. With up to 9 input images, it can:

Style transfer — Take the artistic style from one image and apply it to the content of another. Upload a painting as the style reference and a photo as the content source, then describe the desired output.

Element swapping — Replace specific objects or characters between images. "Replace the jacket in image 1 with the jacket from image 2" is the kind of instruction the model understands.

Multi-reference fusion — Blend elements from multiple source images into a single coherent output. Useful for mood boarding, character design exploration, and product variation generation.

Restyling — Pass a source image and describe a style transformation: "restyle this product photo as a painterly illustration with warm tones."

Wan 2.7 comes in two variants. Here's when to choose each:

Wan 2.7 Image — Faster generation, max 2K resolution. Best for quick iterations, draft-quality outputs, and workflows where turnaround speed matters more than maximum resolution.

Wan 2.7 Image Pro (this model) — Up to 4K resolution, same thinking mode, same multi-image editing and image set generation. Best for final outputs, production-ready assets, and any work where maximum detail and resolution are required.

Both models support identical features (thinking mode, up to 9 input images, up to 12 image set outputs) — the difference is maximum resolution and generation speed.

For 4K text-to-image — 4K resolution is only available without input images and without image set mode. If you're uploading reference images, max resolution is 2K.

For image editing — Put the editing instruction in your prompt field, not in a separate description. "Apply the color palette from image 1 to the scene in image 2" is the right format. The model reads the prompt as the instruction and the uploaded images as the material to work with.

For image sets — Use structured prompts that describe each image in the set. "Image 1: frontal view. Image 2: side profile. Image 3: three-quarter view." The model uses this structure to generate each frame with consistent visual identity.

For complex prompts — Trust thinking mode. Don't try to simplify prompts to make them easier for the model. Wan 2.7 Image Pro is designed for detailed, multi-element descriptions — the more specific you are, the better the output.

Resolution vs speed — Start at 1K (10 credits) for composition testing. Once you have the generation you want, regenerate at 4K (20 credits) for the final asset.