Jiggle Up | Trending Video Effects API

Jiggle Up Effect

Requirements

Number of Images

Required
Only supports uploading one image

Number of People

Only supports realistic or anime-style single female photos

Image Requirements

The effect is better when the subject is shown from the front and includes at least the upper body or the full body

Prompt

Required
Try not to change the format
If there are personalized needs, you can make changes to the prompt while keeping the structure and most of the content unchanged

Effect Boundaries

There may be cases where the breast-jiggling motion is not obvious or appears more like a hip-twisting movement

Best Practices

Use clear, front-facing photos
Ensure subject is clearly visible
Use upper body or full body shots for optimal results
Keep the default prompt structure
Use single female photos only

Jiggle Up API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/video-effects/jiggle-up 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 Jiggle Up below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/video-effects/jiggle-up" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "image": "https://example.com/your-input.jpg"
}'

# 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("video-effects/jiggle-up", {
        "image": "https://example.com/your-input.jpg"
});

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

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "video-effects/jiggle-up",
    {
    "image": "https://example.com/your-input.jpg"
}
)

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

Jiggle Up API — Frequently asked questions

What is the Jiggle Up API?

Jiggle Up is a Video Effects model for AI inference, exposed as a REST API on WaveSpeedAI. Jiggle-Up transforms photos into natural, expressive jiggling videos with lifelike motion and emotion via Image-to-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 Jiggle Up 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/video-effects/video-effects-jiggle-up.

How much does Jiggle Up cost per run?

Jiggle Up starts at $0.20 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 Jiggle Up accept?

Key inputs: `image`. 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/video-effects/video-effects-jiggle-up.

How long does Jiggle Up take to generate?

Average end-to-end generation time on WaveSpeedAI is around 384 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Jiggle Up outputs commercially?

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

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