alibaba/wan2.7-image-pro-edit

Parameters

Pricing

Unit: $/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-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-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/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/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.
• 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. [Strengths] It provides high-quality style transfer and image modification up to 2K resolution based on a reference image. [Best For] Highly recommended for: high-res style transfer and general image editing. [Limitations] Do NOT use this model for complex multi-element fusion (use Omni Image instead). [Routing] Use this by default for standard image-to-image tasks.
• minimax/minimax-image-01-i2i: [Core Function] MiniMax Image-01 I2I is an image-to-image editing and variation model. [Strengths] It excels at generating new images based on a text prompt while structurally referencing one or more input images. [Best For] Highly recommended for: style transfer, generating variations of existing artwork, and structurally guided image creation. [Limitations] Do NOT use this model if you want to generate video or if you do not have a reference image. [Routing] Use this model when the user provides a reference image and a text prompt to generate a new 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.
• kling/kling-v3-omni-image: [Core Function] Kling V3 Omni Image is a unified multimodal image generation endpoint. [Strengths] It supports complex element extraction and character consistency, allowing you to generate series of images with consistent subjects/elements using <image_N> syntax. [Best For] Highly recommended for: generating comic books, character design sheets, and maintaining strict visual consistency across multiple generations. [Limitations] Do NOT use this model for simple, single-shot text-to-image tasks. [Routing] Use this model when the user requests ‘consistent characters’ or needs to fuse multiple image elements into a new scene.
• 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.
• alibaba/qwen-image-2.0-pro-edit: [Core Function] Qwen Image 2.0 Pro Edit is a highly controllable professional image editing model. [Strengths] It seamlessly unifies generation and editing, supporting NEGATIVE prompts during the editing process to strictly exclude elements. [Best For] Highly recommended for: precise image editing where specific elements must be removed or avoided. [Limitations] Does not feature the explicit ‘Thinking Mode’ reasoning of Wan 2.7. [Routing] Route to this model specifically when the user wants to edit an image AND provides a ‘negative prompt’ to exclude elements.
• 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.
• bytedance/seedream-4.5-i2i: [Core Function] Seedream 4.5 I2I is a high-fidelity image editing model. [Strengths] It provides high-consistency, high-resolution style transfer and image-to-image transformations. [Best For] Highly recommended for: professional aesthetic modifications and high-resolution edits. [Limitations] Lacks the advanced reasoning of 5.0 Lite. [Routing] Use this for pure aesthetic/high-fidelity edits.