Vidu Q3 Text-to-Video turns text prompts into high-quality videos with exceptional visual fidelity and diverse motion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$0.35per run·~28 / $10
The two were arguing fiercely in English when the woman angrily slapped the man hard across the face.
A retro taxi driving slowly on a rainy New York street at night, neon lights reflecting on the wet pavement, pedestrians with umbrellas walking hurriedly, camera tracking the taxi, cinematic film grain, photorealistic, 8k, moody atmosphere.
Gentle 2D slice of life anime. Students laughing and walking down a school hallway filled with sunlight during sunset. Warm color palette, soft watercolor background textures, relaxed atmosphere, expressive character designs.
Vibrant 3D anime idol concert. A group of female idols dancing and singing on a glittering stage with large LED screens playing graphics. cheering crowd with lightsticks. Flashy visual effects, smooth motion capture animation, bright and colorful stage lighting.
Vidu Q3 Text-to-Video is an advanced AI video generation model that creates high-quality videos directly from text descriptions. With support for multiple styles, resolutions up to 1080p, and optional audio generation, it delivers cinematic results with smooth motion and rich detail.
Multiple styles Choose between general realistic style or anime aesthetic.
High resolution output Generate videos in 540p, 720p, or 1080p quality.
Flexible duration Create videos from 1 to 16 seconds in length.
Audio generation Optional synchronized audio and background music.
Motion control Adjust movement amplitude for subtle or dynamic animations.
Prompt Enhancer Built-in tool to automatically improve your video descriptions.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the video scene and action |
| style | No | Visual style: general (default), anime |
| resolution | No | Output quality: 540p, 720p (default), 1080p |
| duration | No | Video length in seconds (1-16, default: 5) |
| aspect_ratio | No | Output ratio: 16:9, 4:3, 9:16, etc. |
| movement_amplitude | No | Motion intensity: auto (default), small, medium, large |
| generate_audio | No | Generate synchronized audio (default: enabled) |
| bgm | No | Add background music (default: enabled) |
| seed | No | Random seed for reproducibility (-1 for random) |
| Resolution | Cost per second |
|---|---|
| 540p | $0.07 |
| 720p | $0.15 |
| 1080p | $0.16 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/vidu/q3/text-to-video 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 Q3 Text To Video below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/vidu/q3/text-to-video" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"style": "general",
"resolution": "720p",
"duration": 5,
"aspect_ratio": "4:3",
"movement_amplitude": "auto",
"generate_audio": true,
"bgm": true,
"seed": 0
}'
# 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/q3/text-to-video", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"style": "general",
"resolution": "720p",
"duration": 5,
"aspect_ratio": "4:3",
"movement_amplitude": "auto",
"generate_audio": true,
"bgm": true,
"seed": 0
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"vidu/q3/text-to-video",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"style": "general",
"resolution": "720p",
"duration": 5,
"aspect_ratio": "4:3",
"movement_amplitude": "auto",
"generate_audio": true,
"bgm": true,
"seed": 0
}
)
print(output["outputs"][0]) # → URL of the generated outputQ3 Text To Video is a Vidu model for video generation, exposed as a REST API on WaveSpeedAI. Vidu Q3 Text-to-Video turns text prompts into high-quality videos with exceptional visual fidelity and diverse motion. 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-q3-text-to-video.
Q3 Text To Video starts at $0.35 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`, `aspect_ratio`, `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-q3-text-to-video.
Average end-to-end generation time on WaveSpeedAI is around 510 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.