Wan 2.1 V2V 720P Ultra Fast | AI Video Enhancement API

Wan 2.1 V2V 720p Ultra Fast — wavespeed-ai/wan-2.1/v2v-720p-ultra-fast

Wan 2.1 V2V 720p Ultra Fast is a speed-optimized video-to-video model that transforms an input video using a text prompt while preserving the original motion and timing. Upload a source video, describe the desired changes (style, lighting, environment, details), and tune strength to control how closely the output follows the original footage. This variant is the non-LoRA version, built for fast, clean V2V iteration at 720p.

Key capabilities

Ultra-fast video-to-video transformation anchored to an input video (720p output)
Prompt-guided edits while keeping motion continuity and pacing
Strength control to balance preservation vs. transformation
Fine motion behavior tuning via flow_shift for smoother motion
Efficient for rapid A/B testing with different prompts and seeds

Use cases

Rapid 720p V2V restyling for social, ads, and creative iteration
Mood and lighting changes (cinematic grade, warm window light, neon, noir)
Brand-safe refresh: keep composition and timing, update textures/colors/details
Consistent motion preservation when you only need prompt-driven changes
Fast iteration before upgrading to higher resolution or LoRA workflows

Pricing

Duration	Price per video
5s	$0.225
10s	$0.3375

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)

A clean structure is “preserve + edit + constraints”:

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 composition. Apply a candid, cinematic look with warm sunlight, soft depth of field, and gentle film grain.
Preserve timing and camera movement. Restyle the scene into a clean anime look with stable shading and no flicker.
Keep the same scene and people. Shift the color grade to golden hour and add subtle bloom while maintaining realistic shadows.

Wan 2.1 v2v 720p Ultra Fast API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-720p-ultra-fast 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 Ultra Fast below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-720p-ultra-fast" \
  -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-ultra-fast", {
        "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-ultra-fast",
    {
    "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 Ultra Fast API — Frequently asked questions

What is the Wan 2.1 v2v 720p Ultra Fast API?

Wan 2.1 v2v 720p Ultra Fast is a WaveSpeedAI model for video editing, exposed as a REST API on WaveSpeedAI. Ultra-fast Wan 2.1 V2V generates unlimited 720P video-to-video conversions and supports custom LoRAs for personalized styles. 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 Ultra Fast 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-ultra-fast.

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

Wan 2.1 v2v 720p Ultra Fast starts at $0.23 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 Ultra Fast 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-ultra-fast.

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

Average end-to-end generation time on WaveSpeedAI is around 132 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 Ultra Fast 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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