Kling VIDEO 2.6 Pro
Kling VIDEO 2.6 Pro is a full audio-visual AI video model that combines cinematic-quality video generation with native audio (dialogue, sound effects, ambience). It supports flexible workflows from text or image input, delivering synchronized video and sound in one pass with strong consistency and creative control. Via the API, Motion Control enables creators to guide character movement using a reference video for more realistic and physically grounded motion.
API Options
Platform-level options for task execution and delivery.
-
taskType
string required value: videoInference -
Identifier for the type of task being performed
-
taskUUID
string required UUID v4 -
UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.
-
outputType
string default: URL -
Video output type.
Allowed values 1 value
-
outputFormat
string default: MP4 -
Specifies the file format of the generated output. The available values depend on the task type and the specific model's capabilities.
- `MP4`: Widely supported video container (H.264), recommended for general use.
- `WEBM`: Optimized for web delivery.
- `MOV`: QuickTime format, common in professional workflows (Apple ecosystem).
Allowed values 3 values
-
outputQuality
integer min: 20 max: 99 default: 95 -
Compression quality of the output. Higher values preserve quality but increase file size.
-
webhookURL
string URI -
Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.
Learn more 1 resource
- Webhooks PLATFORM
- Webhooks
-
deliveryMethod
string default: async -
Determines how the API delivers task results.
Allowed values 1 value
- Returns an immediate acknowledgment with the task UUID. Poll for results using getResponse. Required for long-running tasks like video generation.
Learn more 1 resource
- Task Polling PLATFORM
-
uploadEndpoint
string URI -
Specifies a URL where the generated content will be automatically uploaded using the HTTP PUT method. The raw binary data of the media file is sent directly as the request body. For secure uploads to cloud storage, use presigned URLs that include temporary authentication credentials.
Common use cases:
- Cloud storage: Upload directly to S3 buckets, Google Cloud Storage, or Azure Blob Storage using presigned URLs.
- CDN integration: Upload to content delivery networks for immediate distribution.
// S3 presigned URL for secure upload https://your-bucket.s3.amazonaws.com/generated/content.mp4?X-Amz-Signature=abc123&X-Amz-Expires=3600 // Google Cloud Storage presigned URL https://storage.googleapis.com/your-bucket/content.jpg?X-Goog-Signature=xyz789 // Custom storage endpoint https://storage.example.com/uploads/generated-image.jpgThe content data will be sent as the request body to the specified URL when generation is complete.
-
safety
object -
Content safety checking configuration for video generation.
Properties 2 properties
-
safety»checkContentcheckContent
boolean default: false -
Enable or disable content safety checking. When enabled, defaults to
fastmode.
-
safety»modemode
string default: none -
Safety checking mode for video generation.
Allowed values 3 values
- Disables checking.
- Checks key frames.
- Checks all frames.
-
-
ttl
integer min: 60 -
Time-to-live (TTL) in seconds for generated content. Only applies when
outputTypeisURL.
-
includeCost
boolean default: false -
Include task cost in the response.
-
numberResults
integer min: 1 max: 4 default: 1 -
Number of results to generate. Each result uses a different seed, producing variations of the same parameters.
Inputs
Input resources for the task (images, audio, etc). These must be nested inside the inputs object.
inputs object.-
inputs»frameImagesframeImages
array of strings or objects min items: 1max items: 2 -
An array of frame-specific image inputs to guide video generation. Each item can be either a plain image input (UUID, URL, Data URI, or Base64) or an object that pairs an image with a target frame position.
The
frameImagesparameter allows you to constrain specific frames within the video sequence, ensuring that particular visual content appears at designated points. This is different fromreferenceImages, which provide overall visual guidance without constraining specific timeline positions.When the
frameparameter is omitted, automatic distribution rules apply:- 1 image: Used as the first frame.
- 2 images: First and last frames.
Examples 3 examples
Shorthand format: When you don't need to specify a frame position, you can pass a plain image input directly.
"frameImages": [ "aac49721-1964-481a-ae78-8a4e29b91402" ]Object format: When you need to specify a frame position, use an object with
imageandframe.First and last frames: With two images, they automatically become the first and last frames of the video sequence. You can mix shorthand and object formats."frameImages": [ { "image": "aac49721-1964-481a-ae78-8a4e29b91402", "frame": "first" } ]"frameImages": [ "aac49721-1964-481a-ae78-8a4e29b91402", { "image": "3ad204c3-a9de-4963-8a1a-c3911e3afafe", "frame": "last" } ]Format 1: string[]
-
Image input (UUID, URL, Data URI, or Base64).
Format 2: object[] 2 properties
-
inputs»frameImages»imageimage
string required -
Image input (UUID, URL, Data URI, or Base64).
-
inputs»frameImages»frameframe
object -
Target frame position for the image. Supports first and last frame.
Allowed values 4 values
- First frame of the video.
- Last frame of the video.
- Frame index 0 (first frame).
- Frame index -1 (last frame).
-
inputs»referenceVideosreferenceVideos
array of strings items: 1 -
List of reference videos (UUID, URL).
Generation Parameters
Core parameters for controlling the generated content.
-
model
string required value: klingai:kling-video@2.6-pro -
Identifier of the model to use for generation.
Learn more 3 resources
-
positivePrompt
string required min: 2 max: 2500 -
Text prompt describing elements to include in the generated output.
Learn more 2 resources
-
negativePrompt
string min: 2 max: 2500 -
Prompt to guide what to exclude from generation. Ignored when guidance is disabled (CFGScale ≤ 1).
Learn more 1 resource
-
Width of the generated media in pixels.
Learn more 2 resources
-
Height of the generated media in pixels.
Learn more 2 resources
-
duration
float default: 5 -
Length of the generated video in seconds. The total number of frames produced is determined by duration multiplied by the model's frame rate (fps).
Allowed values 2 values
-
CFGScale
float min: 0 max: 1 step: 0.01 default: 0.5 -
Guidance scale representing how closely the output will resemble the prompt. Higher values produce results more aligned with the prompt.
Learn more 1 resource
Provider Settings
Parameters specific to this model provider. These must be nested inside the providerSettings.klingai object.
providerSettings.klingai object.-
providerSettings»klingai»characterOrientationcharacterOrientation
string -
Source for character orientation reference.
Allowed values 2 values
- Match orientation from the reference image.
- Match orientation from the reference video.
-
providerSettings»klingai»keepOriginalSoundkeepOriginalSound
boolean default: false -
Maintain the original sound from the reference video.
-
providerSettings»klingai»soundsound
boolean default: false -
Enable native audio generation.
Luminous Ice Cavern Pilgrimage
{
"taskType": "videoInference",
"taskUUID": "b13b5e2e-5ee4-4fd6-a59e-2759ac18ad37",
"model": "klingai:kling-video@2.6-pro",
"positivePrompt": "A solitary pilgrim advances deeper into an immense crystal ice cavern, robes brushing the frozen path, tiny lantern in hand casting warm amber flickers against towering translucent formations. The camera begins near the traveler and glides forward into the chamber, revealing refracted turquoise light, drifting frost motes, subtle crunching footsteps, soft fabric movement, echoing droplets, low cavern resonance, and a distant humming choir-like wind. The scene feels sacred, majestic, and immersive, with cinematic realism, strong depth, volumetric light, natural motion, and synchronized environmental audio.",
"negativePrompt": "low detail, blurry textures, jittery motion, duplicated limbs, deformed hands, cartoon style, flat lighting, abrupt camera shake, crowded scene, modern objects, text, watermark",
"duration": 10,
"CFGScale": 0.6,
"providerSettings": {
"klingai": {
"sound": true
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/33a9e037-dd42-405c-9172-30d4fdf64f7e.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "b13b5e2e-5ee4-4fd6-a59e-2759ac18ad37",
"videoUUID": "722c22e5-c587-4ede-b050-9728e4704749",
"videoURL": "https://vm.runware.ai/video/os/a02d21/ws/5/vi/722c22e5-c587-4ede-b050-9728e4704749.mp4",
"cost": 1.4
}Rain-Soaked Tram Depot Reverie
{
"taskType": "videoInference",
"taskUUID": "4df4c7a0-d468-444a-b63e-6823dd3f6f80",
"model": "klingai:kling-video@2.6-pro",
"positivePrompt": "A cinematic early-morning tram depot in an old coastal metropolis after a storm, wide shot shifting into intimate detail, wet steel tracks reflecting amber signal lamps, a cream-and-crimson tram gliding in with sparks humming overhead, commuters in tailored rain capes and folded umbrellas, a street violinist under the station awning playing a wistful melody, puddles rippling from light drizzle, gulls circling beyond distant warehouses and harbor cranes, steam rising from vents, realistic human motion, subtle camera drift, layered depth, expressive faces, polished filmic lighting, natural ambience with tram brakes, electrical buzz, footsteps on wet pavement, soft conversation, violin music blending with rain and harbor sounds, emotionally resonant, elegant, contemporary cinematic realism",
"negativePrompt": "low resolution, blurry faces, distorted anatomy, extra limbs, frozen motion, flicker, text overlays, subtitles, watermark, logo, oversaturated colors, cartoon style, chaotic crowding, broken tram geometry, duplicated people, harsh strobe lighting, silent scene",
"width": 1920,
"height": 1080,
"duration": 10,
"CFGScale": 0.7,
"providerSettings": {
"klingai": {
"sound": true
}
}
}{
"taskType": "videoInference",
"taskUUID": "4df4c7a0-d468-444a-b63e-6823dd3f6f80",
"videoUUID": "c8b3cdfe-935c-44c2-9f6b-398c43a62d09",
"videoURL": "https://vm.runware.ai/video/os/a19d05/ws/5/vi/c8b3cdfe-935c-44c2-9f6b-398c43a62d09.mp4",
"cost": 1.4
}Marble Observatory Sprint Sequence
{
"taskType": "videoInference",
"taskUUID": "dfa0301c-f40a-4337-84d2-2e3c5cabb6c3",
"model": "klingai:kling-video@2.6-pro",
"positivePrompt": "A cinematic wide-shot sequence in a vast open-air marble observatory above a sea of clouds at sunrise, concentric celestial map floors, towering brass armillary structures, fluttering measurement banners, and long warm shadows. A young courier in a cobalt coat sprints along the circular gallery carrying a glowing sealed message tube, then slows near the central platform as giant rings rotate overhead. The camera begins with a sweeping lateral track, transitions into a low-angle follow shot behind the runner, then arcs upward into a majestic reveal of the entire observatory. Hyper-detailed stone textures, elegant fabric motion, realistic human movement, dynamic depth, atmospheric haze, expressive lighting, cinematic composition. Native audio: echoing footsteps on polished marble, rushing wind through the arches, distant metallic chimes from rotating instruments, soft cloth flaps, the courier's breathing, and a brief whispered line: 'I'm not too late.'",
"negativePrompt": "low resolution, blurry details, warped anatomy, extra limbs, duplicate person, stiff motion, jittery camera, flat lighting, overexposed highlights, muddy shadows, distorted architecture, text, watermark, logo, subtitle, frame glitches, compression artifacts, cropped subject, deformed hands, unnatural face, chaotic background, unrelated vehicles, modern city skyline, heavy fog obscuring scene",
"width": 1920,
"height": 1080,
"duration": 10,
"CFGScale": 0.76,
"providerSettings": {
"klingai": {
"sound": true
}
}
}{
"taskType": "videoInference",
"taskUUID": "dfa0301c-f40a-4337-84d2-2e3c5cabb6c3",
"videoUUID": "a22de691-0470-4d6e-9105-d8afdcce0a3b",
"videoURL": "https://vm.runware.ai/video/os/a14d18/ws/5/vi/a22de691-0470-4d6e-9105-d8afdcce0a3b.mp4",
"cost": 1.4
}Rainy Neon Underpass Duet
{
"taskType": "videoInference",
"taskUUID": "80bc2705-9b70-45cc-92cd-b8792ec2e387",
"model": "klingai:kling-video@2.6-pro",
"positivePrompt": "Transform the provided first-frame image into a 10-second cinematic scene. A lone violinist performs beneath a futuristic transit underpass during a rainy night, with passing trains sending pulses of colored light across wet pavement. The camera begins close and slowly arcs sideways, revealing depth in the tunnel, distant commuters, rippling reflections, drifting mist, and vibrating violin strings. Her performance becomes more intense, and the environment responds subtly: footsteps echo, droplets fall from overhead beams, a train rushes by with a metallic roar, and the underpass ambience surrounds the scene. Native audio should feature emotional solo violin in sync with bow movement, soft station announcements muffled in the distance, rain drips, electrical hum, train movement, and realistic urban reverberation. Maintain photoreal detail, stable character identity, coherent hand motion, natural body mechanics, cinematic contrast, and immersive atmosphere.",
"negativePrompt": "low resolution, blurry face, distorted hands, extra limbs, duplicate person, flickering anatomy, unrealistic bow motion, cartoon, text overlay, watermark, subtitles, oversaturated glow, chaotic camera shake, broken reflections, deformed instrument, crowd blocking subject",
"duration": 10,
"CFGScale": 0.5,
"providerSettings": {
"klingai": {
"sound": true
}
},
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/7b390e88-10fc-402a-92de-55d9d5fca28f.jpg",
"frame": "first"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "80bc2705-9b70-45cc-92cd-b8792ec2e387",
"videoUUID": "dcc390ae-66c7-4f26-bca3-b048b9b204e4",
"videoURL": "https://vm.runware.ai/video/os/a07d11/ws/5/vi/dcc390ae-66c7-4f26-bca3-b048b9b204e4.mp4",
"cost": 1.4
}Rain-Glossed Tram Terminal Reverie
{
"taskType": "videoInference",
"taskUUID": "ca762297-e35c-4ccb-b4a0-5c49faf1a5b3",
"model": "klingai:kling-video@2.6-pro",
"positivePrompt": "Transform the first frame into the last frame with elegant cinematic motion and strong scene consistency. The camera slowly glides forward through a vast rain-swept tram terminal with reflective stone floors and a vaulted glass canopy. A solitary violinist in a cobalt coat becomes the emotional anchor of the scene as sparse travelers drift past in soft focus. Ripples spread through puddles, amber lamps shimmer in reflections, hanging signs sway slightly, and fine rain at the entrance gradually softens into luminous dawn mist. As the sequence progresses, folded paper swans appear and drift across the shallow water, leading the eye toward a vintage tram preparing to depart. End with the violinist stepping onto the tram as warm early light replaces the cooler tones. Naturalistic motion, physically believable transitions, rich atmosphere, detailed reflections, subtle fabric movement, restrained cinematic drama.",
"negativePrompt": "low detail, flicker, jitter, warped anatomy, duplicate people, extra limbs, deformed hands, broken reflections, chaotic motion, abrupt cuts, heavy motion blur, oversaturated colors, text, logos, watermark",
"duration": 10,
"CFGScale": 0.5,
"inputs": {
"frameImages": [
{
"image": "https://assets.runware.ai/assets/inputs/a2d8c3cf-69b5-4b15-9926-50ce4a9c3f9b.jpg",
"frame": "first"
},
{
"image": "https://assets.runware.ai/assets/inputs/ad9d7952-2f80-4c21-8627-b5061eb89183.jpg",
"frame": "last"
}
]
}
}{
"taskType": "videoInference",
"taskUUID": "ca762297-e35c-4ccb-b4a0-5c49faf1a5b3",
"videoUUID": "cfd59960-2880-42a9-a56d-6c2482e19de0",
"videoURL": "https://vm.runware.ai/video/os/a24d12/ws/5/vi/cfd59960-2880-42a9-a56d-6c2482e19de0.mp4",
"cost": 0.7
}