alibaba/wan-2.7-pro/text-to-image

text-to-image

PRO

Generates images from text prompts with Wan 2.7 image pro, supporting higher fidelity outputs and 4K-ready workflows.

INPUT

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OUTPUT

Idle

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Your request will cost 0.075 per run. For $10 you can run this model approximately 133 times.

Here's what you can do next:

Image-to-Video Image-to-Image

Parameters

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Integrations

Input Schema

The following parameters are accepted in the request body.

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Example Request Body

json

{
  "model": "alibaba/wan-2.7-pro/text-to-image"
}

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Alibaba WAN 2.7 Pro Text-to-Image

Alibaba WAN 2.7 Pro Text-to-Image is the higher-fidelity Wan 2.7 text generation tier. Compared with the standard model, it is better suited to richer detail, cleaner composition, and larger-format output workflows.

What makes it stand out?

Higher fidelity output: Better suited for scenes with dense detail, stronger material rendering, and cleaner structure.
4K-ready text generation: Official Wan 2.7 image documentation allows 4K output for text-only generation on the Pro model.
Creative controls: Supports flexible sizing, grouped generation, and repeatable exploration with seed control.
Production-oriented route: Better fit for polished marketing, concept art, and premium visual generation workflows.

Designed For

Teams preparing campaign visuals and presentation-ready hero images.
Creators who need more detail and stronger composition than the standard model.
Product and brand teams targeting high-resolution image deliverables.
Creative teams and professionals who need a stronger premium-quality text-to-image model.

Recommended size guidance:

Use 4K only for pure text-to-image generation.
For ordinary workflows, 2K remains the safest default.

How to Use

Describe the desired scene with enough detail to benefit from the Pro tier.
Choose 2K for most work, or 4K when you need larger text-only output.
Use thinking mode when visual reasoning and composition quality matter most.
Review the outputs and select the version that best matches your creative goal.

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