Wan 2.1 t2v-480p-lora generates unlimited 480P text-to-video outputs with custom LoRAs for personalized styles and precise control. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.2per run·~50 / $10
ExamplesView all
B0x13ng Boxing video sexy female boxers, athletic women, intense fight, boxing gloves, sweat, slow motion, fierce expressions, toned bodies, action scene, dramatic lighting, cinematic
Oil painting style,VanGogh,VanGogh style. A missile fired at the moon, which exploded.
VanGogh,VanGogh style. An older man with a beard and a wide-brimmed hat is sitting indoors. Behind him are several landscape paintings depicting various outdoor scenes.He looked up and touched his hat
l3g0_5ty13 Lego animation style, a close-up shot of a Lego minifigure with sunglasses and a black leather jacket, sitting inside a Lego sports car. His hands grip the tiny steering wheel, and the dashboard has tiny glowing screens. The background is a blurry city filled with neon Lego signs.
u1tr4_w1d3, ultra wide angle shot A single sailboat is sailing across a stormy sea. The camera captures the vastness of the ocean and the small size of the boat, with dark clouds filling the sky.
masterpiece, best quality, ultra-detailed, photorealistic, 8K UHD, RAW photo,a beautiful 20-year-old Japanese girl, standing on a bustling street in Shinjuku, Tokyo at night, glowing neon signs and light trails from traffic in the background, she is wearing a stylish modern jacket, looking at the camera with a slight smile,cinematic lighting, soft volumetric light, sharp focus on her face, shallow depth of field, bokeh,shot on Canon EOS R5 with a 85mm f/1.2 lens, ISO 1600, realistic skin texture, detailed eyes.
masterpiece, best quality, photorealistic, incredibly detailed, emotional photograph. A touching portrait of an elderly couple in their 70s, walking hand-in-hand on a sandy beach at sunset. The man wears a simple button-up shirt and trousers, while the woman is in a comfortable summer dress. They are viewed from a slight distance, walking away from the camera towards the setting sun, their silhouettes gently outlined by the warm, orange light. Their faces show wrinkles that tell a story of a life lived together, with expressions of contentment and peace. The waves are gently lapping at the shore. Shot with a Canon EOS R6 and a 70-200mm f/2.8 lens to compress the background and create an intimate, cinematic feel.
action shot of a teenage boy skateboarding on the street, wearing a loose hoodie and cargo pants. the photo captures him mid-air during a jump, full of energy. background is a city graffiti wall, dynamic composition, slight motion blur. street photography style, wide-angle lens, bright sunlight, high contrast, vivid colors.
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README
Wan 2.1 AI Video Model
We present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features:
- 👍 SOTA Performance: Wan2.1 consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks.
- 👍 Multiple Tasks: Wan2.1 excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation.
- 👍 Visual Text Generation: Wan2.1 is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications.
- 👍 Powerful Video VAE: Wan-VAE delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation.
Wan 2.1 T2v 480p Lora API — Quick start
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/t2v-480p-lora 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 T2v 480p Lora below.
HTTP example
# 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/t2v-480p-lora" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"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.Node.js example
// 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);
try {
const result = await client.run("wavespeed-ai/wan-2.1/t2v-480p-lora", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"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;
}Python example
# pip install wavespeed
import os
from wavespeed import Client
client = Client(api_key=os.environ["WAVESPEED_API_KEY"])
try:
output = client.run(
"wavespeed-ai/wan-2.1/t2v-480p-lora",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"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 T2v 480p Lora API — Frequently asked questions
What is the Wan 2.1 T2v 480p Lora API?
Wan 2.1 T2v 480p Lora is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Wan 2.1 t2v-480p-lora generates unlimited 480P text-to-video outputs with custom LoRAs for personalized styles and precise control. 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 T2v 480p Lora 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-t2v-480p-lora.
How much does Wan 2.1 T2v 480p Lora cost per run?
Wan 2.1 T2v 480p Lora 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 Wan 2.1 T2v 480p Lora accept?
Key inputs: `prompt`, `duration`, `size`, `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-t2v-480p-lora.
How long does Wan 2.1 T2v 480p Lora take to generate?
Average end-to-end generation time on WaveSpeedAI is around 84 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 T2v 480p Lora 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.