Attributes
- Provider: alibaba
- Category: Image Editing
Series
Parameters
| Name | Description | Type | Required | Enums |
|---|---|---|---|---|
| prompt | Image editing instruction, supports Chinese and English | string | Yes | - |
| images | Input image URLs or Base64 strings (1-9 images). Formats: JPEG, JPG, PNG, BMP, WEBP. Resolution: [240, 8000] px per side, aspect ratio [1:8, 8:1], max 20MB per image | string[] | Yes | - |
| size | Output resolution. Preset: 1K, 2K. Or custom pixels (format: widthheight, range [768768, 2048*2048]). Max 2K for image editing | string | No | - |
| enable_sequential | Enable sequential mode for generating coherent multi-image sets from image input | boolean | No | true, false |
| n | Number of images. Default mode (enable_sequential=false): 1-4, default 4. Sequential mode (enable_sequential=true): 1-12, default 12. Directly affects cost | integer | No | - |
| seed | Random seed for reproducible results | integer | No | - |
Pricing
Unit: $/img
| Pricing |
|---|
| $0.0185/img |
Related Models
- alibaba/wan2.7-image: [Core Function] Wan 2.7 Image is a fast, reasoning-enhanced image generation model. [Strengths] It includes the chain-of-thought reasoning and text rendering of the Pro version, but is optimized for speed, supporting up to 2K resolution. [Best For] Highly recommended for: fast iterations, conceptual design, and generating accurate images with text at standard resolutions. [Limitations] Do NOT use this model if you require 4K print-ready resolution. [Routing] Use this for standard, everyday high-quality image generation requests.
- alibaba/wan2.7-image-pro: [Core Function] Wan 2.7 Image Pro is Alibaba’s flagship reasoning-enhanced image generation model. [Strengths] It features built-in chain-of-thought reasoning (Thinking Mode), exceptional prompt accuracy, native 12-language text rendering, and generates ultra-high-resolution 4K images. [Best For] Highly recommended for: print-ready large-format posters, complex logical prompts, and generating images containing specific text/typography. [Limitations] Do NOT use this model if you need to generate batch images rapidly (use Wan 2.7 Image instead) or if you specifically need negative prompts (use Qwen Image 2.0 Pro). [Routing] Use this model by default for high-end, 4K, or text-heavy image generation tasks.
- alibaba/wan2.7-image-pro-edit: [Core Function] Wan 2.7 Image Pro Edit is Alibaba’s flagship reasoning-enhanced image editing model. [Strengths] It supports interactive editing, character-consistent multi-image generation, and complex multi-reference modifications with deep reasoning. [Best For] Highly recommended for: professional image retouching, consistent character sheets, and complex structural edits. [Limitations] Do NOT use this model if you specifically need to use negative prompts to exclude elements during editing (use Qwen Image 2.0 Pro Edit instead). [Routing] Use this by default for high-end image editing and multi-reference consistent character generation.
- alibaba/wan2.7-t2v: [Core Function] Wan 2.7 T2V is Alibaba’s flagship text-to-video generation model. [Strengths] It generates high-fidelity video directly from text with support for custom aspect ratios, audio generation, and intricate semantic adherence. [Best For] Highly recommended for: high-quality commercial video generation, professional storytelling, and dynamic cinematic sequences. [Limitations] Do NOT use this model if the user specifically requests the streamlined ‘HappyHorse’ workflow. [Routing] Use this model by default for high-end text-to-video requests on the Alibaba platform.
- alibaba/wan3.0-t2v: [Core Function] Wan 3.0 T2V is Alibaba Wan 3.0 text-to-video generation with optional document or webpage reference. [Strengths] It generates up to 30-second video at 480P/720P/1080P with controllable aspect ratio and optional output audio, and can ground generation on a file or public webpage. [Best For] Highly recommended for: pure text-to-video storytelling, product ads driven by pptx/pdf briefs, turning public articles into short videos, and square or vertical social clips. [Limitations] At least one of prompt, file_url, or link_url is required; an empty body is rejected. Do NOT pass file_url and link_url together. Do NOT use this model if the user provides images or videos as primary media; route those to Wan 3.0 I2V or V2V. [Routing] Prefer this model for Wan 3.0 text-only or file/link-to-video. Use Wan 3.0 I2V for first-frame or reference-image workflows, and Wan 3.0 V2V when reference video is required.
- alibaba/wan2.7-i2v: [Core Function] Wan 2.7 I2V is Alibaba’s flagship multimodal image-to-video model. [Strengths] It supports multimodal input (text, image, audio, video) for first-frame, start-and-end-frame (FL2V), and video continuation tasks. [Best For] Highly recommended for: complex image animation, cinematic transitions, and video extension workflows. [Limitations] Do NOT use this model if you only need a quick, simple animation where HappyHorse might be faster. [Routing] Use this model by default for complex image-to-video or video continuation tasks.
- alibaba/wan3.0-i2v: [Core Function] Wan 3.0 I2V is Alibaba Wan 3.0 image-to-video generation supporting first-frame, first-last-frame, and reference-image modes. [Strengths] It can strictly lock the first and last frames or fuse up to 10 reference images with optional reference audio for multimodal guidance. [Best For] Highly recommended for: animating a single keyframe, cinematic first-to-last transitions, multi-image character or product consistency, and image-led storytelling. [Limitations] Do NOT use this model for text-only generation, document/webpage reference, or when a reference video is required. Do NOT mix first_frame/last_frame with reference_images/audio_urls. [Routing] Prefer this model for Wan 3.0 image-driven video. Use Wan 3.0 T2V for prompt/file/link inputs and Wan 3.0 V2V when video_urls are provided.
- alibaba/wan2.7-r2v: [Core Function] Wan 2.7 Reference-to-Video is a highly capable character/entity reference video model. [Strengths] It natively supports entity reference, voice customization, and playbook-based video generation from a single storyboard. [Best For] Highly recommended for: creating consistent video series, brand mascot animation, and storyboard-driven storytelling. [Limitations] Do NOT use this model for simple, single-image direct animation (use I2V instead). [Routing] Use this by default for complex character consistency and storyboard generation tasks on Alibaba.
- alibaba/wan2.7-videoedit: [Core Function] Wan 2.7 Video Editing is an instruction-based video modification model. [Strengths] It supports complex video editing tasks like content replacement using reference images, and replicating actions, effects, and camera movements. [Best For] Highly recommended for: modifying existing video footage, style transfer on videos, and targeted element replacement. [Limitations] Do NOT use this model to generate a brand new video from scratch; it requires an input video. [Routing] Use this model by default whenever a user wants to edit, alter, or restyle an existing video.
- alibaba/wan3.0-v2v: [Core Function] Wan 3.0 V2V is Alibaba Wan 3.0 reference-video generation that builds new video from one or more input videos. [Strengths] It supports up to 5 reference videos with optional reference images and audio for multimodal composition and prompt-referenced subjects. [Best For] Highly recommended for: video-to-video transformation, multi-subject scenes that cite video1/image1 in the prompt, and extending creative edits from existing clips. [Limitations] Do NOT use this model for text-only, file/link, or first-frame-only workflows. video_urls is required. [Routing] Prefer this model when the user supplies reference video. Use Wan 3.0 T2V for prompt/file/link and Wan 3.0 I2V for image-first generation.
