Wan 2.1 i2v 480p Ultra-Fast generates unlimited image-to-video content at 480p, supporting custom LoRAs for style personalization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Inactivo
$0.125por ejecución·~80 / $10
Felt doll spinning on grassy field, r0t4tion 360 degrees rotation
Girl takes off bikini bottom and turns to show nude ass
The video starts with a close-up of a smiling man in a blue button-down shirt, then the 8r1d3 bride effect happens. The man is now in a white lace wedding dress, smiling, with a bouquet of white flowers in front of a blurred wooden background.
A man with short brown hair wearing a white shirt and a dark coat stands in the red neon light of a motel room doorway. He looks back towards the motel room. The camera performs a cr34sh crash zoom in effect, rapidly zooming closer to the man's face. He turns with a shocked expression, as if he heard a noise, and reaches for his pocket.
The video begins with an image of purple Thanos from Marvel. Then the v1p red carpet transformation appears. Purple Thanos is shown wearing a black dress, with gold jewelry around his neck and ears. The image is again of purple Thanos looking straight at the camera against a more lighted gray background. The v1p red carpet transformation continues, purple Thanos is now on the red carpet with photographers taking pictures and other people behind a barricade to the sides. Purple Thanos is wearing the same black dress and jewelry, in focus at the center of the frame.
The video depicts a coastal road during a storm, where a large black armored SUV and a black police car drive closely together. Lightning flashes overhead during the c4r ch4s3 car chase. The camera moves forward, initially tracking alongside the SUV, then transitioning to a view behind the police car, showcasing its pursuit of the SUV as they navigate the winding road. The wet asphalt reflects the vehicle's headlights.
An intense, dynamic close-up of a muscular man in his 30s, his face glistening with sweat and showing intense concentration, performing a heavy deadlift in a gritty gym. The video shows his muscles tensing and the weight lifting off the ground. The lighting is dramatic and high-contrast, with spotlights creating deep shadows. The atmosphere is raw and powerful. Documentary style, super slow-motion, sharp focus on the man's expression, professional video quality.
A photo of the back of a young woman, standing on a high-rise balcony, facing a vibrant city skyline at night. Her hands are resting on the railing as she gazes at the distant neon lights. A gentle breeze moves her long hair, conveying a sense of quiet contemplation. The scene has a cool, urban color palette, captured with a cinematic wide-angle shot from slightly behind the subject. The background features a dynamic, blurred motion of city lights.
A photo of the back of a middle-aged man, sitting by the window of a vintage coffee shop, looking out at the rain. He holds a cup of coffee, his posture relaxed. The window reflects his faint silhouette, and raindrops are slowly running down the glass. The camera is a static close-up, focused on the person's profile and the mesmerizing rhythm of the rain outside. The style is nostalgic and melancholic, creating a pensive, introspective mood.
A photo of the back of a backpacker, slowly walking down a sun-dappled forest path. Dressed in outdoor gear and carrying a large backpack, their posture is relaxed and steady. Sunlight filters through the leaves, creating a beautiful pattern of light and shadow on the ground. The camera performs a smooth tracking shot, following the person from behind. The overall style is natural and serene, with soft light and warm tones, evoking a sense of exploration.
A low-angle, artistic shot of the back of a painter, a woman in her 50s, standing in her sunlit studio. She is hunched over a canvas, brush in hand, with her back to the camera. The video captures the subtle movement of her hand as she paints. Dust motes dance in the diffused light coming from a large window. The scene is filled with canvases, jars of paint, and a sense of creative focus. The style is cinematic, with a painterly feel, warm tones, and a peaceful,
A tense, over-the-shoulder shot from behind a young athlete, showing the back of a basketball coach, a man in his 40s, giving instructions during a game. The coach's hands are gesturing emphatically. The background is a blur of a brightly lit basketball court and cheering fans. The video focuses on the slight shifts in the coach's posture and the energy of his movements. The style is high-energy, documentary-like, with sharp focus on the coach and a dynamic feel, as if the camera is part of the action.
Wan 2.1 I2V 480p LoRA Ultra Fast is a fast, cost-efficient image-to-video model that animates a single reference image into a short clip guided by your prompt. It supports LoRA injection so you can enforce a specific motion/style/character look while keeping generation lightweight—great for rapid iteration, previews, and high-volume variants.
| Resolution | Duration | Price per run | Effective price per second |
|---|---|---|---|
| 480p | 5s | $0.125 | $0.025/s |
| 480p | 10s | $0.188 | $0.019/s |
Keep the prompt like a director note:
Felt doll standing on a grassy field. The doll slowly rotates for a full 360-degree turn with smooth motion, stable framing, no jitter. Soft daylight, shallow depth of field, gentle background bokeh.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/i2v-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 I2v 480p Lora Ultra Fast below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/i2v-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",
"image": "https://example.com/your-input.jpg",
"negative_prompt": "blurry, low quality, distorted",
"loras": [
{
"path": "Remade-AI/Rotate",
"scale": 1
}
],
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"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].// 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/i2v-480p-lora-ultra-fast", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"negative_prompt": "blurry, low quality, distorted",
"loras": [
{
"path": "Remade-AI/Rotate",
"scale": 1
}
],
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 3,
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/wan-2.1/i2v-480p-lora-ultra-fast",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"negative_prompt": "blurry, low quality, distorted",
"loras": [
{
"path": "Remade-AI/Rotate",
"scale": 1
}
],
"size": "832*480",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 3,
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputWan 2.1 I2v 480p Lora Ultra Fast is a WaveSpeedAI model for AI inference, exposed as a REST API on WaveSpeedAI. Wan 2.1 i2v 480p Ultra-Fast generates unlimited image-to-video content at 480p, supporting custom LoRAs for style 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.
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-i2v-480p-lora-ultra-fast.
Wan 2.1 I2v 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.
Key inputs: `prompt`, `image`, `duration`, `size`, `seed`, `guidance_scale`. 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-i2v-480p-lora-ultra-fast.
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.
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.