Wan 2.1 V2V 480p is an ultra-fast video-to-video model that generates unlimited AI videos and supports custom LoRAs for personalization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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$0.125실행당·~80 / $10
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A pixel-art animation of a red-suited chibi character jumping between floating platforms in a bright blue sky. The motion is bouncy and playful, with pixel particle effects on each jump. The camera follows smoothly with slight shake to enhance the retro arcade game feel.
An anime-style video of a pink-haired high school girl walking slowly under cherry blossom trees. The petals fall gently around her as the camera follows her from the side with a soft dolly shot. Her expression is peaceful, her skirt and hair moving naturally in the spring breeze. The background is softly blurred, with warm pastel lighting.
The woman in the image slowly turns toward the camera and smiles, hair gently moving in the breeze, sunlight flickering"
A fantasy-themed video of a cloaked traveler seen from behind, standing motionless on a cliff edge. The camera slowly pulls back and rises to reveal the floating island in the sky, surrounded by drifting clouds and ethereal light. The mood is mysterious and epic, with orchestral music vibes.
The character in the image starts singing emotionally on a small spotlighted stage, camera slowly zooming in on her face
The subject walks slowly through a crowded market street at night, lens flare from passing headlights, immersive ambiance
The camera rotates around the frozen figure as their clothing slowly melts into animated paint strokes
A slow motion shot of a woman walking through a street market at sunset, soft golden light reflecting off fresh produce and colorful textiles, vendors chatting and people smiling in the background. The camera gently tracks her from behind as her hair sways.
The character dissolves into flower petals that spiral upward into the sky, surreal and magical ambiance
The person in the image begins to dissolve into liquid chrome, reflections warping around a moving camera
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README
Wan 2.1 V2V 480p LoRA Ultra Fast — wavespeed-ai/wan-2.1/v2v-480p-lora-ultra-fast
Wan 2.1 V2V 480p LoRA Ultra Fast is a speed-optimized video-to-video model for prompt-guided edits while preserving the original motion and timing of an input video. Upload a source video, describe what should change, and tune strength to control how closely the output follows the original footage. It supports up to 3 LoRAs to enforce a consistent style, character look, or branded aesthetic—now with lower latency for rapid iteration.
Key capabilities
- Ultra-fast video-to-video transformation anchored to an input video (480p output)
- Prompt-guided edits while keeping motion continuity and pacing
- Strength control to balance preservation vs. transformation
- LoRA support (up to 3) for stable style/identity steering
- Fine control over motion behavior via flow_shift
Use cases
- Rapid V2V restyling for social clips and creative iteration
- Apply a consistent “house style” across multiple clips using LoRAs
- Lighting/mood changes (cinematic grade, neon, golden hour) without re-animating motion
- Brand-safe refresh: keep composition and timing, update textures/colors/details
- Quick A/B testing by changing prompts, LoRAs, or seed
Pricing
| Duration | Price per video |
|---|---|
| 5s | $0.125 |
| 10s | $0.1875 |
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)
- loras (optional): up to 3 LoRA items for style/identity steering
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)
LoRA (up to 3 items):
-
loras: list of LoRA entries (max 3)
-
path: owner/model-name or a direct.safetensors URL
-
scale: LoRA strength
Prompting guide (V2V)
Write prompts that explicitly separate preservation from transformation:
Template: Keep the same camera motion and timing from the input video. Change [style/lighting/environment]. Keep faces natural and consistent. Avoid flicker and warping.
Example prompts
- Keep the original motion and composition. Apply a candid, cinematic look with warm sunlight, soft depth of field, and natural skin texture.
- Preserve timing and camera movement. Restyle into a clean anime look with consistent shading and no flicker.
- Keep the same scene and people. Change the color grade to sunset golden hour, add subtle lens flare, maintain realistic shadows.
Wan 2.1 v2v 480p Lora 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-lora-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 480p Lora Ultra Fast below.
HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/v2v-480p-lora-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",
"loras": [
{
"path": "motimalu/wan-flat-color-v2",
"scale": 1
}
],
"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-480p-lora-ultra-fast", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"video": "https://example.com/your-input.mp4",
"loras": [
{
"path": "motimalu/wan-flat-color-v2",
"scale": 1
}
],
"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 outputPython example
# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/wan-2.1/v2v-480p-lora-ultra-fast",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"video": "https://example.com/your-input.mp4",
"loras": [
{
"path": "motimalu/wan-flat-color-v2",
"scale": 1
}
],
"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 outputWan 2.1 v2v 480p Lora Ultra Fast API — Frequently asked questions
What is the Wan 2.1 v2v 480p Lora Ultra Fast API?
Wan 2.1 v2v 480p Lora Ultra Fast is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Wan 2.1 V2V 480p is an ultra-fast video-to-video model that generates unlimited AI videos and supports custom LoRAs for personalization. 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 Lora 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-480p-lora-ultra-fast.
How much does Wan 2.1 v2v 480p Lora Ultra Fast cost per run?
Wan 2.1 v2v 480p Lora 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 Lora 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-lora-ultra-fast.
How long does Wan 2.1 v2v 480p Lora Ultra Fast take to generate?
Average end-to-end generation time on WaveSpeedAI is around 50 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 480p Lora 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.