Wan 2.1 V2V 720P | AI Video Enhancement API

Wan 2.1 V2V 720p — wavespeed-ai/wan-2.1/v2v-720p

Wan 2.1 V2V 720p 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. It’s a solid default choice when you want higher clarity than 480p and don’t need LoRA.

Key capabilities

Video-to-video transformation anchored to an input video (720p 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

Use cases

Restyle a video while keeping original motion (cinematic, dreamy, stylized looks)
Improve mood/lighting (sunset grade, neon night, warm indoor) without changing timing
Brand-safe refresh: keep composition, update colors/textures/details
Social and marketing variations from the same base footage
Quick iteration: change prompts and seeds to generate multiple creative takes

Pricing

Duration	Price per video
5s	$0.30
10s	$0.45

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)

Write prompts that explicitly separate preservation from transformation:

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 dance motion and camera timing. Apply a warm golden-hour cinematic color grade, soft bloom from streetlights, subtle film grain, and realistic shadows.
Preserve motion and composition. Restyle the scene into a clean illustrated look with stable edges and no flicker.
Keep the same choreography and timing. Add light rain, wet pavement reflections, and moody neon lighting while maintaining natural skin tones.

Wan 2.1 v2v 720p API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-720p with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Wan 2.1 v2v 720p below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-720p" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://example.com/your-input.mp4",
    "negative_prompt": "blurry, low quality, distorted",
    "num_inference_steps": 30,
    "duration": 5,
    "strength": 0.9,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("wavespeed-ai/wan-2.1/v2v-720p", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "video": "https://example.com/your-input.mp4",
        "negative_prompt": "blurry, low quality, distorted",
        "num_inference_steps": 30,
        "duration": 5,
        "strength": 0.9,
        "guidance_scale": 5,
        "flow_shift": 3,
        "seed": -1
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "wavespeed-ai/wan-2.1/v2v-720p",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://example.com/your-input.mp4",
    "negative_prompt": "blurry, low quality, distorted",
    "num_inference_steps": 30,
    "duration": 5,
    "strength": 0.9,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}
)

print(output["outputs"][0])  # → URL of the generated output

Wan 2.1 v2v 720p API — Frequently asked questions

What is the Wan 2.1 v2v 720p API?

Wan 2.1 v2v 720p is a WaveSpeedAI model for video editing, exposed as a REST API on WaveSpeedAI. Wan 2.1 V2V converts source videos into AI 720p outputs for scalable video-to-video production and unlimited video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Wan 2.1 v2v 720p API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.1-v2v-720p.

How much does Wan 2.1 v2v 720p cost per run?

Wan 2.1 v2v 720p starts at $0.30 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Wan 2.1 v2v 720p accept?

Key inputs: `prompt`, `video`, `duration`, `seed`, `guidance_scale`, `num_inference_steps`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.1-v2v-720p.

How long does Wan 2.1 v2v 720p take to generate?

Average end-to-end generation time on WaveSpeedAI is around 174 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Wan 2.1 v2v 720p outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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