Kwaivgi Kling V2.0 T2V Master

Playground

Kling 2.0 is the latest AI video model from Kling AI that improves upon its predecessor, the Kling 1.6 model. This new release features improved prompt understanding, enhanced character motion dynamics, greater visual quality, and even a ‘Multi-Elements Editor’ that makes video editing more accessible, flexible, and efficient.

Features

Kling 2.0 Key Features

Enhanced Prompt Adherence

Kling 2.0 interprets complex user prompts with sequential actions more precisely than ever. It can accurately understand intricate character actions, delicate expressions, and advanced camera movements, allowing professional-grade control over visual sequences.

Better Motion Dynamics

Kling 2.0 supports a greater motion range with more natural and fluid character movements. It generates immersive sequences simulating complex motions with realistic detail.

Improved Visual Aesthetics

Kling 2.0 produces higher-quality videos featuring richer details and more accurate visual style control. It enables cinematic-level sequences with dramatic expressions and consistent styles using reference images.

Multi-Elements Editor

Kling 2.0 introduces a powerful video editor that allows users to add, swap, or delete video content using text or image inputs. Users can swap elements such as clothing or even entire subjects, enabling greater customization and creative control.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.0-t2v-master" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "prompt": "Capture a dynamic, high-speed chase scene featuring two motorcycles navigating through a bustling cityscape at night. The camera alternates between close-up shots of the riders' intense expressions, the glowing neon signs of the city, and the sleek lines of the motorcycles as they weave through traffic. The sound of revving engines and the hum of the city create an exhilarating atmosphere.",
    "aspect_ratio": "16:9",
    "duration": "5"
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

Parameter	Type	Required	Default	Range	Description
prompt	string	Yes		-	Text prompt for generation; Positive text prompt; Cannot exceed 2500 characters.
aspect_ratio	string	No	16:9	-	Generated video aspect ratio.
negative_prompt	string	No		-	Negative text prompt; Cannot exceed 2500 characters.
duration	string	No	5	5, 10	The duration of the generated media in seconds.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Query Parameters

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction, the ID of the prediction to get
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Kwaivgi Kling V2.0 I2v Master Kwaivgi Kling V2.1 I2v Master