Wan 2.1 V2V 480p

Playground

WAN 2.1 V2V (video-to-video) converts source clips into unlimited AI-generated 480p videos for scalable content creation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.1 V2V 480p — wavespeed-ai/wan-2.1/v2v-480p

Wan 2.1 V2V 480p is a video-to-video model for prompt-guided transformations while preserving the original motion and timing of an input clip. Upload a source video, describe the desired changes (style, lighting, atmosphere, details), and tune strength to control how closely the output follows the original footage. This 480p variant is ideal for fast, low-cost iteration before upgrading to 720p or LoRA workflows.

Key capabilities

Video-to-video transformation anchored to an input video (480p output)
Preserves motion continuity and pacing from the original clip
Prompt-guided edits for style, lighting, mood, and scene details
Strength control to balance “keep original” vs. “transform”
Motion behavior tuning via flow_shift for smoother motion

Use cases

Low-cost V2V restyling for rapid iteration and ideation
Mood/lighting changes (cinematic grade, warm indoor, neon night) without retiming
Social clip variations from the same base footage
Draft previews before running higher resolution versions
Generating multiple takes quickly by changing prompt or seed

Pricing

Duration	Price per video
5s	$0.20
10s	$0.30

Inputs

video (required): source video to transform
prompt (required): what to change and how the result should look
negative_prompt (optional): what to avoid (artifacts, jitter, unwanted elements)

Parameters

num_inference_steps: sampling steps
duration: output duration (seconds)
strength: how strongly to transform the input video (lower = preserve more; higher = change more)
guidance_scale: prompt adherence strength
flow_shift: motion/flow behavior tuning
seed: random seed (-1 for random; fixed for reproducible results)

Prompting guide (V2V)

Template: Keep the original motion and timing. Change [style/lighting/environment/details]. Keep faces stable and natural. Avoid flicker, warping, and jitter.

Example prompts

Keep the original motion and timing. Apply a warm cinematic color grade, soft bloom, subtle film grain, and natural shadows.
Preserve composition and camera movement. Restyle into a clean anime look with stable shading and no flicker.
Keep the same scene and movement. Add light rain and wet reflections while maintaining realistic skin tones.

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/wavespeed-ai/wan-2.1/v2v-480p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "num_inference_steps": 30,
    "duration": 5,
    "strength": 0.9,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}'

# 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
video	string	Yes		-	The video for generating the output.
prompt	string	Yes		-
negative_prompt	string	No		-	The negative prompt for the generation.
num_inference_steps	integer	No	30	1 ~ 40	The number of inference steps to perform.
duration	integer	No	5	5 ~ 10	The duration of the generated media in seconds.
strength	number	No	0.9	0.10 ~ 1.00
guidance_scale	number	No	5	0.00 ~ 20.00	The guidance scale to use for the generation.
flow_shift	number	No	3	1.0 ~ 10.0	The shift value for the timestep schedule for flow matching.
seed	integer	No	-1	-1 ~ 2147483647	The random seed to use for the generation. -1 means a random seed will be used.

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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