Vidu Q2 Turbo Image-to-Video turns a single image into smooth, cinematic motion with fast, high-quality output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
就绪
$0.1每次运行·~10 / $1
A cinematic fantasy sequence. The boy gently reaches out to touch the colorful dragon’s nose, and the dragon slowly lowers its head, blinking warmly. Soft dust particles float in the air, light beams shimmer through mist, and the ground subtly breathes with glowing mushrooms. The camera slowly circles around them, capturing the magical bond between child and creature in a gentle, emotional moment. Highly detailed, volumetric lighting, soft depth of field, 4K quality.
A serene snowy night at an elevated Japanese train station, bathed in deep blue twilight. A lone child in a blue coat and red backpack stands on the empty platform, looking down the tracks. Above, a massive cherry blossom tree reflects perfectly on a mirror-like snowy surface, petals gently drifting in the cold wind. Soft overhead station lights cast warm glows on concrete pillars. Subtle steam rises from the child's breath. Camera slowly dollies forward from wide establishing shot to medium on the child, with delicate snow particles floating in air. Hyper-detailed Makoto Shinkai anime style, cinematic color grading, 6-second poetic loop, 1080p, 16:9.
Epic fantasy procession in a windswept flower field. A blonde samurai girl in ornate teal armor stands atop a massive yellow ox demon with curved horns and red ropes. Wind whips her hair and cape. Behind, a blindfolded monk with staff and a rat-eared monk with tail walk in sync. Red spider lilies sway violently. Camera slow dolly left, low angle, ox’s heavy steps shake the ground. Hand-painted ukiyo-e anime style, saturated colors, dynamic ink textures
Cyber-dystopian alley at dusk. A lone girl with ultra-long orange ponytail in flowing white tech-coat walks away from camera. Her coat billows in wind, cables overhead sway like vines. Sunlight cuts through skyscraper gaps, casting golden beams on cracked concrete. Camera slow tracking shot behind her, slight parallax on buildings. Photorealistic CGI, teal-orange color grade, volumetric god rays
Epic anime mountain standoff. A blonde girl in red hooded cloak grips a glowing katana, eyes fierce. Behind her, a young archer notches an arrow. A colossal white wolf with scarred mask towers, fur rippling in wind. Clouds swirl around snow-capped peaks. Camera slow push-in from wide tableau to tight on girl and wolf’s eyes, scarf and mane dancing. Studio Ghibli-style hand-drawn animation, soft cel-shading, golden rim light
Vidu Q2 Turbo Image-to-Video turns a single reference image into a smooth, cinematic video. Turbo accelerates generation for faster turnaround while keeping motion clean and stable — great for transitions, product demos, and quick storytelling.
Turbo-optimized pipeline Faster generation than Pro at the same settings, perfect for quick iteration.
Temporal smoothing Cuts flicker and popping while keeping faces, hands, hair, and thin details intact.
Depth-aware motion Respects occlusion and parallax for natural foreground/background separation.
Cinematic camera paths Subtle pans, push-ins, and dollies without rubbery warps.
Optional background music Auto-generate BGM for social-ready clips.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Reference image to animate (upload or URL) |
| prompt | Yes | Describe desired motion, mood, and camera movement |
| duration | No | Video length in seconds (1–10, default: 4) |
| resolution | No | Output resolution: 540p, 720p, or 1080p |
| movement_amplitude | No | Motion intensity: auto, small, medium, or large |
| bgm | No | Enable background music generation |
| seed | No | Random seed for reproducibility (-1 for random) |
| Resolution | Duration | Price |
|---|---|---|
| 540p | 1s | $0.03 |
| 540p | 2s | $0.04 |
| 540p | 3s | $0.05 |
| 540p | 4s | $0.06 |
| 540p | 5s | $0.07 |
| 540p | 6s | $0.08 |
| 540p | 7s | $0.09 |
| 540p | 8s | $0.10 |
| 540p | 9s | $0.20 |
| 540p | 10s | $0.30 |
| 720p | 1s | $0.04 |
| 720p | 2s | $0.05 |
| 720p | 3s | $0.10 |
| 720p | 4s | $0.15 |
| 720p | 5s | $0.20 |
| 720p | 6s | $0.25 |
| 720p | 7s | $0.30 |
| 720p | 8s | $0.35 |
| 720p | 9s | $0.45 |
| 720p | 10s | $0.50 |
| 1080p | 1s | $0.175 |
| 1080p | 2s | $0.225 |
| 1080p | 3s | $0.275 |
| 1080p | 4s | $0.325 |
| 1080p | 5s | $0.375 |
| 1080p | 6s | $0.425 |
| 1080p | 7s | $0.475 |
| 1080p | 8s | $0.525 |
| 1080p | 9s | $0.625 |
| 1080p | 10s | $0.725 |
540p: $0.03 for 1s, +$0.01/s up to 8s, then $0.20 for 9s, $0.30 for 10s
720p: $0.04 for 1s, $0.05 for 2s, then +$0.05/s from 3s
1080p: $0.175 for 1s, then +$0.05/s up to 8s, then +$0.10/s for 9s-10s
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/vidu/image-to-video-q2-turbo 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 Image To Video Q2 Turbo below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/vidu/image-to-video-q2-turbo" \
-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",
"duration": 5,
"resolution": "720p",
"bgm": true,
"movement_amplitude": "auto",
"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("vidu/image-to-video-q2-turbo", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"duration": 5,
"resolution": "720p",
"bgm": true,
"movement_amplitude": "auto",
"seed": -1
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"vidu/image-to-video-q2-turbo",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"image": "https://example.com/your-input.jpg",
"duration": 5,
"resolution": "720p",
"bgm": true,
"movement_amplitude": "auto",
"seed": -1
}
)
print(output["outputs"][0]) # → URL of the generated outputImage To Video Q2 Turbo is a Vidu model for video generation from images, exposed as a REST API on WaveSpeedAI. Vidu Q2 Turbo Image-to-Video turns a single image into smooth, cinematic motion with fast, high-quality output. 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/vidu/vidu-image-to-video-q2-turbo.
Image To Video Q2 Turbo starts at $0.10 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`, `resolution`, `duration`, `seed`, `bgm`. 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/vidu/vidu-image-to-video-q2-turbo.
Average end-to-end generation time on WaveSpeedAI is around 42 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 (Vidu). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.