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Wan 2.1 V2V 480P Ultra Fast

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Ultra-fast Wan 2.1 Video-to-Video (v2v) model for generating unlimited AI videos at 480p from existing video inputs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

video-to-video
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Inactivo

$0.125por ejecución·~80 / $10

Siguiente:

EjemplosVer todo

A woman floats gracefully in the vast expanse of dark outer space, her movements captured in slow motion. The backdrop is a mesmerizing tapestry of twinkling stars, their light piercing through the inky blackness. Distant galaxies shimmer like ethereal jewels, casting a soft glow that outlines her form. Wisps of cosmic dust drift lazily around her, adding a sense of serene stillness to the scene.

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README

Wan 2.1 Video-to-Video 480p Ultra Fast

Wan 2.1 Video-to-Video 480p Ultra Fast is a lightning-fast video transformation model optimized for speed and efficiency. Convert existing videos into new styles and visual treatments in seconds — perfect for rapid iteration, previews, and high-volume processing.

Why It Stands Out

  • Ultra-fast processing: Optimized for speed without sacrificing quality.
  • Video-to-video transformation: Convert videos into different styles while preserving motion.
  • Prompt-guided transformation: Describe the visual style you want to achieve.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Negative prompt support: Exclude unwanted elements for cleaner outputs.
  • Fine-tuned control: Adjust strength, guidance scale, and flow shift for precise results.
  • Affordable pricing: Cost-effective option for prototyping and batch processing.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
videoYesSource video to transform (upload or public URL).
promptYesText description of the desired visual style.
negative_promptNoElements to avoid in the output.
num_inference_stepsNoQuality/speed trade-off (default: 30).
durationNoOutput video length: 5 or 10 seconds (default: 5).
strengthNoTransformation intensity (0.0–1.0, default: 0.9).
guidance_scaleNoPrompt adherence strength (default: 5).
flow_shiftNoMotion flow control (default: 3).
seedNoSet for reproducibility; -1 for random.

How to Use

  1. Upload your source video — drag and drop a file or paste a public URL.
  2. Write a prompt describing the visual style you want. Use the Prompt Enhancer for AI-assisted optimization.
  3. Add a negative prompt (optional) — specify elements to exclude.
  4. Adjust parameters — set strength, guidance scale, and other settings as needed.
  5. Click Run and wait for your video to generate.
  6. Preview and download the result.

Best Use Cases

  • Rapid Prototyping — Quickly test style transformations before committing to higher resolutions.
  • Batch Processing — Transform multiple videos affordably at scale.
  • Style Exploration — Experiment with different visual treatments efficiently.
  • Content Previews — Generate quick previews for client approval.
  • Social Media Content — Create stylized videos for platforms where 480p is sufficient.

Pricing

DurationPrice
5 seconds$0.125
10 seconds$0.1875

Pro Tips for Best Quality

  • Use lower strength (0.5–0.7) to preserve more of the original video.
  • Use higher strength (0.8–0.95) for more dramatic style transformations.
  • Use negative prompts to reduce artifacts like blur, distortion, or unwanted elements.
  • Start with 480p Ultra Fast for testing, then upgrade to 720p for final delivery.
  • Fix the seed when iterating to compare different parameter settings.

Notes

  • Ensure uploaded video URLs are publicly accessible.
  • Processing time is optimized for speed — expect quick turnaround.
  • For higher resolution output, consider Wan 2.1 V2V 720p.
  • Please ensure your content complies with usage guidelines.
Nota:Este sitio web utiliza modelos de IA proporcionados por terceros.

Wan 2.1 v2v 480p 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-480p-ultra-fast with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Wan 2.1 v2v 480p Ultra Fast below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "num_inference_steps": 30,
    "duration": 5,
    "strength": 0.9,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-480p-ultra-fast" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-480p-ultra-fast";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
        "num_inference_steps": 30,
        "duration": 5,
        "strength": 0.9,
        "guidance_scale": 5,
        "flow_shift": 3,
        "seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "num_inference_steps": 30,
    "duration": 5,
    "strength": 0.9,
    "guidance_scale": 5,
    "flow_shift": 3,
    "seed": -1
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-480p-ultra-fast", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Wan 2.1 v2v 480p Ultra Fast API — Frequently asked questions

What is the Wan 2.1 v2v 480p Ultra Fast API?

Wan 2.1 v2v 480p Ultra Fast is a WaveSpeedAI model for video editing, exposed as a REST API on WaveSpeedAI. Ultra-fast Wan 2.1 Video-to-Video (v2v) model for generating unlimited AI videos at 480p from existing video inputs. 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 480p 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/wan-2.1-v2v-480p-ultra-fast.

How much does Wan 2.1 v2v 480p Ultra Fast cost per run?

Wan 2.1 v2v 480p Ultra Fast starts at $0.13 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 480p 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-480p-ultra-fast.

How long does Wan 2.1 v2v 480p Ultra Fast take to generate?

Median end-to-end generation time on WaveSpeedAI is around 90 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Wan 2.1 v2v 480p 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.

Wan 2.1 V2V 480P Ultra Fast | AI Video to Video API | WaveSpeedAI