kling/kling-v3-turbo-t2v

属性

• 提供商: kling
• 类别: 文生视频

系列

• Kling V3

集合

• AI Video Generator

参数

价格

输入图片（$/img）: 0.0000
输入视频（$/sec）: 0.0000

单位: $/sec

相关模型

• 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-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.
• 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-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.
• alibaba/happyhorse-1.1-t2v: [Core Function] HappyHorse 1.1 T2V is Alibaba’s latest streamlined text-to-video model. [Strengths] It generates 720P/1080P video with native audio support, 3-15 second duration, and an expanded set of aspect ratios including 4:5, 5:4, 9:21, and 21:9. [Best For] Highly recommended for: fast HappyHorse text-to-video generation, social video formats, and high-throughput content creation. [Limitations] It does not expose custom audio controls; use Wan 2.7 T2V when custom audio input is required. [Routing] Prefer this model when the user explicitly requests HappyHorse text-to-video or wants the latest HappyHorse generation quality.
• 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.
• bytedance/seedance-2.0-t2v: [Core Function] Seedance 2.0 T2V is ByteDance Dreamina Seedance 2.0 text-to-video. [Strengths] Supports 480p/720p/1080p/4k, 24 fps, 4-15s MP4 output. Text-only input — do not pass images, video, or audio. [Routing] Use for high-fidelity text-to-video when quality or 4k output is requested.
• xai/grok-imagine-video: [Core Function] Grok Imagine Video is xAI’s text-to-video generation model. [Strengths] It excels at generating short, dynamic video clips directly from a text prompt, with controllable duration, aspect ratio, and resolution. [Best For] Highly recommended for: short social clips, animated concepts, and dynamic scene generation from a description. [Limitations] Do NOT use this model when you have a starting image or reference subjects, or when you need resolutions above 720p or clips longer than 15 seconds; it is limited to 480p/720p and 15s. [Routing] Use this model when the user wants a video from text only. If a starting image is provided, route to the Image-to-Video model; for reference-driven character video, use Reference-to-Video.
• xai/grok-imagine-video-1.5-i2v: [Core Function] Grok Imagine Video 1.5 I2V animates a single starting image into a video using the Grok Imagine 1.5 generation backbone. [Strengths] It excels at producing motion from one starting frame with the improved 1.5 model. [Best For] Highly recommended for: animating a photo or illustration when the 1.5 generation backbone is preferred. [Limitations] Do NOT use this model for text-only generation, for resolutions above 1080p, or for clips longer than 15 seconds; it requires a starting image and is limited to 480p/720p/1080p and 15s. [Routing] Use this model when the user provides one starting image and prefers the 1.5 backbone.
• bytedance/seedance-2.0-i2v: [Core Function] Seedance 2.0 I2V is ByteDance’s flagship unified multimodal video generation model. [Strengths] It supports complex mixed references (multiple images, audio clips) and generates up to 15s of multi-shot audio-video output with dual-channel audio. [Best For] Highly recommended for: high-end complex video generation, multi-shot narratives, and mixed-reference cinematic production. [Limitations] Do NOT use this model if you only need a very basic legacy generation without complex references. [Routing] Use this model by default for any complex, multi-reference, or high-fidelity image-to-video tasks.
• alibaba/happyhorse-1.1-i2v: [Core Function] HappyHorse 1.1 I2V is Alibaba’s latest streamlined first-frame image-to-video model. [Strengths] It turns a single image into high-quality 720P/1080P video with native audio support and 3-15 second duration; output aspect ratio follows the first frame image. [Best For] Highly recommended for: rapid image animation, product motion previews, and simple character or scene animation. [Limitations] It does not accept an explicit ratio parameter; use T2V or R2V when you need a fixed generated aspect ratio. [Routing] Prefer this model when the user provides one image and requests HappyHorse image animation.
• alibaba/happyhorse-1.1-r2v: [Core Function] HappyHorse 1.1 R2V is Alibaba’s latest reference-image-to-video model. [Strengths] It uses 1-9 reference images to preserve subject or character appearance while generating new video actions, supports 720P/1080P output, 3-15 second duration, and expanded aspect ratios including 4:5, 5:4, 9:21, and 21:9. [Best For] Highly recommended for: character-consistent storytelling, reference-based product shots, and multi-image subject composition. [Limitations] Do NOT use if the user simply wants to animate a single image exactly as provided; use HappyHorse I2V instead. [Routing] Use when the user provides one or more reference images and asks for a newly generated HappyHorse video.
• 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/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.
• bytedance/seedance-2.0-v2v: [Core Function] Seedance 2.0 V2V is ByteDance’s flagship multimodal video-to-video model. [Strengths] It allows powerful editing and stylization of input videos by supporting mixed references (text, images, video, and audio) and producing multi-shot 15s outputs. [Best For] Highly recommended for: complex video-to-video transformations, restyling existing footage, and creating dynamic multi-shot edits. [Limitations] Do NOT use this model for simple still-image generation (use Seedream instead). [Routing] Use this model by default for any video editing or video-to-video generation tasks.
• 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.
• xai/grok-imagine-video-extend: [Core Function] Grok Imagine Video Extend continues an existing video, generating additional footage beyond its end. [Strengths] It excels at seamlessly extending a clip with new prompt-guided motion. [Best For] Highly recommended for: lengthening short clips, continuing a scene, and adding follow-on action. [Limitations] Do NOT use the duration parameter expecting it to set the total video length; it only controls the length of the appended segment (2-10 seconds). Input video constraints are enforced by the upstream provider. [Routing] Use this model when the user wants to make a video longer. To restyle or modify an existing video, use Video Edit.
• bytedance/seedance-2.5-t2v: [Core Function] Seedance 2.5 T2V is ByteDance Dreamina Seedance 2.5 text-to-video generation. [Strengths] It generates longer clips up to 30 seconds at 480p/720p/1080p with optional mp4 or mov output and native audio generation. [Best For] Highly recommended for: longer-form text-to-video storytelling, social clips beyond 15 seconds, and Seedance workflows that need mov output. [Limitations] Do NOT use this model if the user provides images, video, or audio as inputs. Do NOT use this model when the user requires 4k output. [Routing] Prefer Seedance 2.5 T2V when the user needs more than 15 seconds of text-to-video. Use Seedance 2.0 T2V when 4k is required. Use Seedance 2.5 I2V or V2V when media inputs are provided.
• bytedance/seedance-2.5-v2v: [Core Function] Seedance 2.5 V2V is ByteDance Dreamina Seedance 2.5 video-to-video generation covering multimodal reference, video editing, and video extension. [Strengths] It accepts up to 10 reference videos, 30 reference images, and 10 audio clips, with 480p/720p/1080p, 4-30 second output, and mp4 or mov containers. [Best For] Highly recommended for: editing existing clips, extending motion from a base video, multi-reference restyling, and prompt-driven composition that cites @Video1 or @Image1. [Limitations] Do NOT use this model for text-only or first-frame-only workflows. video_urls is required. Do NOT send first_frame_image or last_frame_image. Do NOT use this model when the user requires 4k output. Do NOT use this model for audio-only input. [Routing] Prefer this model for Seedance 2.5 edit, extension, and video-reference jobs. Use Seedance 2.5 T2V for text-only and Seedance 2.5 I2V for image-first generation.
• 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/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/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.
• vidu/viduq4-r2v: [Core Function] Vidu Q4 R2V is the preview reference-to-video model that composes a new 3-16 second clip from 1 to 15 reference images while keeping subject appearance consistent. [Strengths] It supports 540p through 4K, aspect ratios including 3:4 and 4:3, synchronized audio, and up to three reference audio clips. [Best For] Highly recommended for: multi-image character consistency, vertical 3:4 portraits, and scenes that combine reference images with spoken audio. [Limitations] Do NOT use this model to animate one image exactly as the first frame; use Vidu Q4 I2V for that. Do NOT omit the prompt. Do NOT send more than 15 images or more than 3 audio files. Subject-library invocation is not supported. [Routing] Use this model when the user supplies reference images and a prompt for a newly composed shot. Use Vidu Q4 I2V for a single start frame.