Kwaivgi Kling V2.1 I2V Pro

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Kling 2.1 Pro converts images to professional cinematic videos with enhanced fidelity, precise camera moves and dynamic motion control. Ready-to-use REST inference API, top performance, no coldstarts, affordable pricing.

Features

Kling v2.1 I2V Pro — kwaivgi/kling-v2.1-i2v-pro

Kling v2.1 I2V Pro turns a single reference image into a short, cinematic video clip guided by your prompt. Upload an image, describe the motion (subject + camera + environment), and the model animates the scene while keeping the input image as the visual anchor. Built for stable production use with a ready-to-use REST API, no cold starts, and predictable pricing.

Key capabilities

Image-to-video generation anchored to your input image
Prompt-controlled motion: facial micro-expressions, hair/clothing movement, environment effects
Cinematic camera moves: push-in, orbit, pan, tilt, handheld feel
Supports negative_prompt to reduce artifacts and unwanted styles

Pricing

Duration	Price
5s	$0.45
10s	$0.90
15s	$1.35
20s	$1.80

Inputs

image (required): the reference image used as the visual anchor
prompt (required): describe what moves and how the camera behaves
negative_prompt (optional): describe what to avoid (blur, distortions, artifacts)

Parameters

prompt: motion + scene direction for the clip
negative_prompt: optional “avoid list”
image: input image (upload or URL)
guidance_scale: how strongly motion follows your prompt (lower = more natural, higher = more literal)
duration: video length in seconds

Prompting guide (I2V)

Write prompts like a director’s brief, focusing on motion:

Subject motion: expression change, breathing, walking, turning, hair swaying
Environment motion: wind, rain, fog, particles, light rays
Camera motion: slow push-in, orbit, dolly, handheld micro-shake
Continuity: keep identity, outfit, and scene layout consistent with the input image

Example prompts

A cinematic close-up of a woman laughing on a sunny city street. Her hair sways in the wind, coat fabric subtly moves, warm natural light, shallow depth of field, camera slow push-in, smooth motion, 5 seconds.
Portrait in golden hour. Gentle breeze, subtle facial motion, soft lens flare, handheld micro-sway, realistic skin texture, 5 seconds.
Moody night street scene. Light rain, drifting mist, neon reflections, camera slow orbit around the subject, 5 seconds.

Negative prompt examples

blur, distort, low quality
jitter, warping, melted details, extra limbs
watermark, logo, subtitles, text artifacts

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-v2.1-i2v-pro" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "guidance_scale": 0.5,
    "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		-	The positive prompt for the generation. max length 2500
negative_prompt	string	No		-	The negative prompt for the generation.
image	string	Yes		-	First frame of the video; Supported image formats include.jpg/.jpeg/.png; The image file size cannot exceed 10MB, and the image resolution should not be less than 300*300px.
guidance_scale	number	No	0.5	0.00 ~ 1.00	The guidance scale to use for the generation.
duration	integer	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 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	string	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.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

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