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.
Bezczynny
$0.125za uruchomienie·~80 / $10
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.
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.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Source video to transform (upload or public URL). |
| prompt | Yes | Text description of the desired visual style. |
| negative_prompt | No | Elements to avoid in the output. |
| num_inference_steps | No | Quality/speed trade-off (default: 30). |
| duration | No | Output video length: 5 or 10 seconds (default: 5). |
| strength | No | Transformation intensity (0.0–1.0, default: 0.9). |
| guidance_scale | No | Prompt adherence strength (default: 5). |
| flow_shift | No | Motion flow control (default: 3). |
| seed | No | Set for reproducibility; -1 for random. |
| Duration | Price |
|---|---|
| 5 seconds | $0.125 |
| 10 seconds | $0.1875 |
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 URLs from data.outputs. Examples for Wan 2.1 v2v 480p Ultra Fast below.
# Submit the prediction
curl --fail-with-body --connect-timeout 10 --max-time 60 \
-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 '{
"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
}'
# Wait at least 2 seconds, then poll. Safe GET requests may be retried.
curl --fail-with-body --connect-timeout 10 --max-time 30 \
--retry 4 --retry-all-errors --retry-delay 1 \
-X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# Start at 2 seconds and increase the interval for long-running tasks.
# Stop on completed, failed, cancelled, or timeout.// npm install wavespeed
const { Client } = require('wavespeed');
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
const client = new Client(apiKey, {
maxConnectionRetries: 5,
retryInterval: 1.0,
});
try {
const result = await client.run("wavespeed-ai/wan-2.1/v2v-480p-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
}, {
timeout: 3600,
pollInterval: 2.0,
});
console.log(result.outputs);
} catch (error) {
console.error('Generation failed:', error);
process.exitCode = 1;
}# pip install wavespeed
import os
from wavespeed import Client
client = Client(
api_key=os.environ["WAVESPEED_API_KEY"],
max_connection_retries=5,
retry_interval=1.0,
)
try:
output = client.run(
"wavespeed-ai/wan-2.1/v2v-480p-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
},
timeout=3600.0,
poll_interval=2.0,
)
print(output["outputs"])
except Exception as error:
raise SystemExit(f"Generation failed: {error}") from errorWan 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.
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.
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.
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.
Average end-to-end generation time on WaveSpeedAI is around 54 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
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.