alibaba/wan2.7-image-pro-edit

属性

• 提供商: alibaba
• 类别: 图像编辑

系列

• Wan

集合

• AI Style Transfer
• Face Swap
• Photo Restoration
• Colorize Photo

参数

价格

单位: $/img

相关模型

• 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-edit: [Core Function] Wan 2.7 Image Edit is a fast, reasoning-enhanced image editing model. [Strengths] Provides the robust editing capabilities of the Wan 2.7 architecture with faster turnaround times. [Best For] Highly recommended for: standard image modifications and style transfers. [Limitations] Do NOT use if you need absolute maximum fidelity or negative prompt support. [Routing] Use for standard, fast image editing tasks.
• 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.
• bytedance/seedream-5.0-lite-edit: [Core Function] Seedream 5.0 Lite Edit is a reasoning-enhanced, smart image editing model. [Strengths] It features superior cross-modal understanding and reasoning, allowing for highly accurate, interactive multi-turn image editing with real-time knowledge enhancement. [Best For] Highly recommended for: complex image editing tasks, structural modifications, and edits requiring deep semantic understanding. [Limitations] As a ‘Lite’ model, raw visual rendering might not match the 4.5 tier. [Routing] Use this model by default for complex, reasoning-based image editing tasks.
• kling/kling-v3-i2i: [Core Function] Kling V3 I2I is the flagship image-to-image editing model (POST /images/generations, model_name=kling-v3 with image). [Strengths] High-quality style transfer and editing up to 2K. [Best For] Single-reference image editing. [Limitations] Do NOT send negative_prompt when image is present (officially unsupported). No image_fidelity / image_reference on V3. For multi-image fusion or series, use kling-v3-omni-image. [Routing] Default for standard image-to-image.
• google/nano-banana-2-edit: [Core Function] Nano Banana 2 Edit is a high-speed image editing model. [Strengths] It rapidly modifies existing images or extracts image frames from videos based on text prompts. [Best For] Highly recommended for: rapid style transfer, quick image modifications, and fast creative edits. [Limitations] Do NOT use this model for meticulous photorealistic retouching. [Routing] Use this model by default for fast, creative image editing tasks.
• xai/grok-imagine-image-edit: [Core Function] Grok Imagine Image Edit is xAI’s standard image editing model. [Strengths] It excels at quickly applying prompt-guided edits and style changes to one or more source images. [Best For] Highly recommended for: fast restyling, quick variations, and lightweight image edits. [Limitations] Do NOT use this model when maximum edit fidelity is required; the Quality variant preserves more detail. A maximum of 3 source images is supported. [Routing] Choose this model for fast edits. When the user demands maximum fidelity, route to Grok Imagine Image Edit (Quality).
• xai/grok-imagine-image-quality-edit: [Core Function] Grok Imagine Image Edit (Quality) is xAI’s high-fidelity image editing model. [Strengths] It excels at applying detailed, prompt-guided edits and style transformations to one or more source images while preserving fine detail. [Best For] Highly recommended for: high-quality restyling, detailed inpainting-style edits, and combining up to 3 source images. [Limitations] Do NOT use this model when latency is critical, as it is slower than the standard edit variant; a maximum of 3 source images is supported. [Routing] Use this model by default for quality-sensitive edits. For faster edits, route to Grok Imagine Image Edit (standard).
• pixverse/video-restyle: [Core Function] PixVerse Restyle re-renders an existing video into a new visual style. [Strengths] Consistent style transfer across all frames. [Best For] Turning footage into anime/3D/painterly looks, stylized remixes. [Limitations] Do NOT use this to change content, motion, or add new scenes; it only re-renders the visual style of an existing video. It requires an input video, and you must provide EITHER restyle_id (a preset style code from the PixVerse restyle list) OR restyle_prompt (free-text style, max 2048 chars), not both. [Routing] Use when the user wants to change the look of an existing video. Use restyle_id for an official preset, restyle_prompt for a custom style.
• xai/grok-imagine-video-edit: [Core Function] Grok Imagine Video Edit applies a prompt-guided transformation to an input video. [Strengths] It excels at restyling and modifying an existing video while keeping its original duration and aspect ratio. [Best For] Highly recommended for: restyling clips, applying visual effects, and prompt-driven video edits. [Limitations] Do NOT use this model to change the duration, aspect ratio, or resolution; the output preserves the input video’s duration and aspect ratio, and those parameters are not configurable. Input video constraints (e.g. format/length) are enforced by the upstream provider. [Routing] Use this model when the user provides a video and wants it edited/restyled. To make a video longer, use Video Extend.
• google/gemini-omni-flash-r2v: [Core Function] Gemini Omni Flash R2V (Reference-to-Video) generates a short 720p video guided by up to three reference images via the Interactions API. [Strengths] It fuses the styles, subjects, or elements from multiple reference images (referred to in the text prompt) into a single coherent animated clip with synchronized audio. [Best For] Highly recommended for: blending characters or visual styles from several images, reference-guided creative shots, and multi-subject compositions where the prompt directs how the references combine. [Limitations] Do NOT use this model if you only have a single starting frame (use I2V instead), or if you need 1080p or 4K or clips longer than 10 seconds; it accepts 1 to 3 reference images and outputs 720p up to 10 seconds (16:9 or 9:16). [Routing] Choose this when the user supplies multiple reference images to combine into one video. For single first-frame animation use Gemini Omni Flash I2V; to modify an existing video use Gemini Omni Flash Video Edit.
• google/gemini-omni-flash-video-edit: [Core Function] Gemini Omni Flash Video Edit performs conversational, instruction-driven editing of an existing video via the Interactions API. [Strengths] It applies natural-language edits (changing the scene, mood, style, lighting, background, or time of day) to an input video while preserving the source video’s length and aspect ratio, with synchronized audio. [Best For] Highly recommended for: re-styling or re-lighting an existing clip, changing a video’s setting or atmosphere, and quick instruction-based revisions of a short video. [Limitations] Do NOT use this model to generate a video from scratch (use T2V, I2V, or R2V), and do NOT expect to change the output resolution, aspect ratio, or duration: the output preserves the source video’s aspect ratio and length, and the model does not accept aspectRatio or duration parameters. The source video should be 3 to 10 seconds. [Routing] Choose this only when the user provides an existing video to modify. To create a new video from text or images, use Gemini Omni Flash T2V, I2V, or R2V instead.
• bytedance/seedream-5.0-pro-edit: [Core Function] Seedream 5.0 Pro Edit is a professional-grade single-image editing (I2I) model. [Strengths] It supports interactive precise editing: edit locations can be specified via coordinates, selection boxes, or arrows described in the prompt, with strong element-level control and subject consistency. [Best For] Highly recommended for: precise local retouching, adding/removing/replacing objects at exact positions, style transfer of a single photo, and professional post-editing workflows. [Limitations] Do NOT use this model for text-to-image generation (an input image is required) or for blending multiple reference images; it accepts exactly one input image and outputs exactly one image (no batch or streaming). [Routing] For 2-10 reference images use Seedream 5.0 Pro Multi-Reference; for pure text-to-image use Seedream 5.0 Pro; choose Seedream 5.0 Lite Edit when batch outputs or more than 10 input images are required.
• bytedance/seedream-5.0-pro-multi-reference: [Core Function] Seedream 5.0 Pro Multi-Reference is a professional-grade multi-reference image generation (I2I) model that creates a single image from 2-10 reference images plus a text prompt. [Strengths] It excels at reference consistency, preserving characters, styles, and objects across multiple input images while following complex blending instructions with professional-grade quality. [Best For] Highly recommended for: keeping character or style consistency across references, combining subjects from different images into one scene, placing products into reference scenes, and IP-consistent content creation. [Limitations] Do NOT use this model with fewer than 2 or more than 10 reference images, and do NOT use it for batch generation or streaming; it outputs exactly one image per request. [Routing] For single-image editing use Seedream 5.0 Pro Edit; for text-only generation use Seedream 5.0 Pro; choose Seedream 5.0 Lite Edit when up to 14 reference images or batch outputs are needed.
• alibaba/qwen-image-3.0-pro-edit: [Core Function] Qwen Image 3.0 Pro Edit is an image-to-image editing model for instruction-based edits and multi-image fusion. [Strengths] It accepts 1-3 reference images plus an edit instruction, optional negative prompts, free-form output size (widthheight), intelligent prompt rewrite, 1-6 outputs while preserving subject identity, and long structured edit instructions. [Best For] Highly recommended for: background replacement, outfit or style changes, multi-image fusion, identity-preserving portrait edits, and iterative creative retouching. [Limitations] Do NOT use this for pure text-to-image with no reference images (use Qwen Image 3.0 Pro instead), native 4K output, or thinking-mode reasoning. Keep output total pixels within 512512 to 2048*2048; input images should follow supported formats and size guidance. Do NOT combine very long prompts with multiple reference images and a long negative_prompt if the request may exceed the model input capacity (about 4.5k tokens total across text and images). [Routing] Route here when the user provides reference image(s) and wants Qwen 3.0 edit quality. For text-only generation without images, use Qwen Image 3.0 Pro.
• kling/kling-v3-omni-image: [Core Function] Kling V3 Omni Image is a unified multimodal image generation endpoint (POST /images/omni-image). [Strengths] Multi-image reference, up to 4K, and optional series generation via result_type/series_amount. Use <<<image_N>>> placeholders in prompt. [Best For] Character consistency, fusing multiple reference images, and comic/storyboard series. [Limitations] Element library IDs are not exposed. Default aspect_ratio is 1:1 when omitted. [Routing] Prefer for multi-image fusion or series; use kling-v3-t2i/i2i for standard single-shot generation.
• openai/gpt-image-2-edit: [Core Function] GPT Image 2 Edit is a high-resolution image-to-image editing model. [Strengths] It excels at making high-fidelity edits and style transformations to a single source image based on a text prompt, preserving details at up to 4K resolutions. [Best For] Highly recommended for: professional photo retouching, upscaling style transfers, and modifying high-resolution concept art. [Limitations] Do NOT use this model for multi-image merging (it only accepts one input image). Do NOT use if you need precise input fidelity control or transparent backgrounds. [Routing] Use this model by default when the user wants to edit a single image and prioritize output resolution/quality. If they need to merge multiple images or control the strictness of the edit (fidelity), use GPT Image 1.5 Edit.
• openai/gpt-image-1.5-edit: [Core Function] GPT Image 1.5 Edit is a versatile image-to-image editing and merging model. [Strengths] It excels at complex utility editing tasks, including multi-image merging (up to 16 images), transparent background support, and precise control over how strictly the model adheres to the input image (fidelity control). [Best For] Highly recommended for: merging reference images, editing UI assets, generating variations with strict shape preservation, and creating transparent cutouts. [Limitations] Do NOT use this model if you require 2K or 4K high-resolution outputs, as it is limited to standard resolutions. [Routing] Use this model specifically when the user provides multiple images to combine, requires transparency, or explicitly asks to ‘keep the exact shape’ of the original image (fidelity control). Otherwise, use GPT Image 2 Edit.
• microsoft/mai-image-2.5-edit: [Core Function] MAI Image 2.5 Edit is Microsoft’s flagship image editing model. [Strengths] It excels at applying high-quality, prompt-guided edits and transformations to a single source image. [Best For] Highly recommended for: restyling, object/scene modification, and detailed prompt-driven edits. [Limitations] Do NOT provide more than one source image or non-JPEG/PNG inputs; it accepts exactly one JPEG or PNG image, and output is always PNG. [Routing] Use this model by default for quality-sensitive edits. For faster, cheaper edits, route to MAI Image 2.5 Flash Edit.