kling/kling-v3-i2i

属性

• プロバイダー: kling
• カテゴリー: 画像編集

シリーズ

• Kling V3

コレクション

• AI Style Transfer
• Image Upscale

パラメーター

料金

単位: $/img

関連モデル

• kling/kling-v3-t2i: [Core Function] Kling V3 T2I is the flagship text-to-image model (POST /images/generations, model_name=kling-v3). [Strengths] High aesthetic quality, prompt adherence, 1K/2K. [Best For] Concept art and photorealistic generation without a reference image. [Limitations] No reference image; for I2I use kling-v3-i2i; for multi-image/series use kling-v3-omni-image. [Routing] Default for Kling text-to-image.
• kling/kling-v3-t2v: [Core Function] Kling V3 T2V is the next-generation text-to-video base model. [Strengths] It natively supports generating ultra-long 15-second videos, 4K resolution, and synchronized native audio directly from text. [Best For] Highly recommended for: high-end cinematic creation, 4K video generation, and creating long-form scenes with integrated sound. [Limitations] Do NOT use this model if you need complex multi-shot narratives or deep physics reasoning; use V3 Omni or Video O1 respectively. [Routing] Use this model by default for high-quality text-to-video tasks that require up to 15 seconds, 4K resolution, or native audio without reference images.
• 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.
• kling/kling-v3-i2v: [Core Function] Kling V3 I2V is the next-generation image-to-video model. [Strengths] It transforms static images into video with support for 4K resolution, 15-second durations, and native audio, providing superior motion and character expressiveness. [Best For] Highly recommended for: animating concept art, bringing portraits to life in 4K, and generating long 15s scenes from a single frame. [Limitations] Do NOT use this model if you need multimodal reference elements (like character consistency across shots) or multi-shot generation; use V3 Omni instead. [Routing] Use this model by default for high-quality single-image-to-video tasks.
• kling/kling-v3-omni-video: [Core Function] Kling V3 Omni Video V2V is a multimodal video-to-video endpoint that edits or restyles existing footage using prompt plus optional image and video references. [Strengths] It focuses on source fidelity and subject consistency for Omni-style edit workflows, combining prompt guidance with images and videos inputs so changes stay grounded in the original clip. [Best For] Highly recommended for: reference-faithful video edits, restyling existing takes, keeping characters or products consistent while changing motion or scene instructions, and short-form post workflows that start from real footage. [Limitations] Do NOT use this model for pure text-to-video from scratch; use Kling V3 T2V, Kling V3 Omni T2V, or Kling V3 Turbo T2V. Do NOT use it when you only have a still image and no source video; use Kling V3 I2V or Kling V3 Omni I2V. Do NOT use it for deep physics-reasoning generation better served by Kling Video O1. [Routing] Choose Kling V3 Omni Video V2V when the user already has video to edit or transform and mentions Omni or multimodal references. Prefer Kling Video O1 when reasoning-heavy generation is the goal rather than source-based editing.
• kling/kling-v3-omni-t2v: [Core Function] Kling V3 Omni T2V is a multimodal-leaning text-to-video model in the V3 family, oriented toward stronger semantic control and subject consistency in prompt-led generation. [Strengths] It targets high-fidelity cinematic clips with native audio options, flexible 3-15s duration, and better adherence when scenes demand coherent characters or multi-beat storytelling from text alone. [Best For] Highly recommended for: narrative T2V with recurring subjects, dialogue-aware scenes, brand or product continuity across beats, and premium short films where consistency matters more than raw throughput. [Limitations] Do NOT use this model if the user only needs the cheapest or fastest clip; prefer Kling V3 Turbo T2V. Do NOT use it when the workflow is image-first or needs multi-image references; use Kling V3 Omni I2V or Kling V3 I2V instead. Do NOT use it for deep physics-reasoning specialty tasks better served by Kling Video O1. [Routing] Choose Kling V3 Omni T2V when the user emphasizes Omni, consistency, multimodal quality, or complex text narratives. Prefer Kling V3 T2V as the default high-quality T2V baseline; prefer Kling V3 Turbo T2V when the user stresses speed, cost, or high-volume short-form output.
• kling/kling-v3-turbo-t2v: [Core Function] Kling V3 Turbo T2V is a speed- and cost-optimized text-to-video model in the V3 family for fast short-form generation. [Strengths] It emphasizes lower latency and efficient throughput with native audio and improved lip-sync for talking-head style clips, typically targeting practical 720p/1080p short videos rather than maximum cinematic headroom. [Best For] Highly recommended for: rapid prototyping, social and ad iteration, batch short-form pipelines, and dialogue clips where turnaround time and unit cost matter most. [Limitations] Do NOT use this model if the user requires peak 4K cinematic fidelity, heavy multi-shot storyboard control, or maximum visual polish; use Kling V3 T2V or Kling V3 Omni T2V instead. Do NOT use it for image-conditioned animation; use Kling V3 Turbo I2V or Kling V3 I2V. [Routing] Choose Kling V3 Turbo T2V when the user says fast, quick, cheap, or high volume. Otherwise default to Kling V3 T2V for quality, or Kling V3 Omni T2V when consistency and Omni-class control are requested.
• kling/kling-v3-omni-i2v: [Core Function] Kling V3 Omni I2V is a multimodal image-to-video model that animates from one or more reference images with stronger subject and style consistency. [Strengths] It accepts an images array for reference-led motion, aiming to preserve identity, wardrobe, and product look across the clip while supporting flexible duration and optional native audio. [Best For] Highly recommended for: character-consistent animation from design sheets, multi-reference product shots, comic or IP look locking, and I2V tasks where a single first frame is not enough. [Limitations] Do NOT use this model for simple one-image animation when cost or speed is the priority; use Kling V3 I2V or Kling V3 Turbo I2V. Do NOT use it when the primary input is text only; use Kling V3 Omni T2V or Kling V3 T2V. Do NOT use it for lip-sync avatar from audio alone; use Kling Avatar. [Routing] Choose Kling V3 Omni I2V when the user asks for Omni, multiple references, or strict visual consistency from images. Prefer Kling V3 I2V for standard single-image high quality; prefer Kling V3 Turbo I2V for fast or cheap single-image jobs.
• kling/kling-v3-turbo-i2v: [Core Function] Kling V3 Turbo I2V is a speed- and cost-optimized image-to-video model that animates a single keyframe into short motion clips. [Strengths] It prioritizes fast turnaround and efficient generation with optional native audio and strong lip-sync for portrait or product first-frame animation at practical resolutions. [Best For] Highly recommended for: animating stills for social ads, rapid keyframe iteration, talking-head starters from one photo, and bulk I2V jobs where latency and cost dominate. [Limitations] Do NOT use this model if the user needs multi-image references, element fusion, or Omni-class subject locking; use Kling V3 Omni I2V. Do NOT use it when maximum 4K cinematic quality is required; use Kling V3 I2V. Do NOT use it for effect templates; use Kling Video Effects. [Routing] Choose Kling V3 Turbo I2V when the user emphasizes speed or cost for single-image animation. Prefer Kling V3 I2V as the default high-quality I2V; prefer Kling V3 Omni I2V when multiple images or consistency-driven references are central.
• 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.
• 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.
• 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.
• 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.
• 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.
• google/nano-banana-pro-edit: [Core Function] Nano Banana Pro Edit is a high-capability creative image editing model. [Strengths] It provides high-quality creative edits, background replacements, and style transformations. [Best For] Highly recommended for: detailed creative modifications and complex style transfers. [Limitations] Do NOT use for strict photorealistic restoration. [Routing] Use this model for detailed, high-quality creative edits.