alibaba/wan2.7-image-pro-edit

属性

• プロバイダー: alibaba
• カテゴリー: 画像編集

シリーズ

• Wan

コレクション

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

パラメーター

料金

単位: $/img

関連モデル

• 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.
• microsoft/mai-image-2.6-edit: [Core Function] MAI Image 2.6 Edit is Microsoft’s latest prompt-guided image editing model in the MAI Image family. [Strengths] It applies targeted edits to a single source image with the same quality gains as MAI Image 2.6 generation. [Best For] Highly recommended for: object edits, layout changes, text cleanup, and iterative photorealistic retouching. [Limitations] Do NOT use this if the caller provides more than one source image, a data URI, or a URL that is not publicly reachable over HTTP or HTTPS. It accepts exactly one JPEG or PNG image URL, and output is always PNG. auto_aspect_ratio and web_grounding are optional booleans; omit them unless the caller sets them. [Routing] Use this model when the latest MAI edit quality is required. For faster or lower-cost edits, route to MAI Image 2.6 Flash Edit.
• microsoft/mai-image-2.6-flash-edit: [Core Function] MAI Image 2.6 Flash Edit is the faster, lower-cost variant of MAI Image 2.6 image editing. [Strengths] It applies prompt-guided edits to a single source image with lower latency than MAI Image 2.6 Edit. [Best For] Highly recommended for: high-throughput edit APIs and production retouching pipelines. [Limitations] Do NOT use this if the caller provides more than one source image, a data URI, or a URL that is not publicly reachable over HTTP or HTTPS. It accepts exactly one JPEG or PNG image URL, and output is always PNG. auto_aspect_ratio and web_grounding are optional booleans; omit them unless the caller sets them. [Routing] Use this model when edit speed or cost matters more than maximum 2.6 quality. For the highest fidelity, route to MAI Image 2.6 Edit.
• openai/gpt-image-2.5-flare-edit: [Core Function] GPT Image 2.5 Flare Edit is a speed-oriented image editing model. [Strengths] Supports up to 16 input images, optional mask-based local edits, resolution tiers up to 4K, and transparent backgrounds. [Best For] Product image changes, masked object replacements, and edits guided by multiple reference images. [Limitations] Do NOT use this for editing more than 16 input images or selecting arbitrary pixel dimensions. Exact input fidelity control is not exposed. [Routing] Choose this variant when speed is the priority; use GPT Image 2.5 Sunburst Edit when image quality is the priority.
• openai/gpt-image-2.5-sunburst-edit: [Core Function] GPT Image 2.5 Sunburst Edit is a quality-oriented image editing model. [Strengths] Supports up to 16 input images, optional mask-based local edits, resolution tiers up to 4K, and transparent backgrounds. [Best For] Product image changes, masked object replacements, and edits guided by multiple reference images. [Limitations] Do NOT use this for editing more than 16 input images or selecting arbitrary pixel dimensions. Exact input fidelity control is not exposed. [Routing] Choose this variant when image quality is the priority; use GPT Image 2.5 Flare Edit when speed is the priority.
• 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.
• 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.