Kling 3.0 Pro delivers top-tier text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and native audio for ready-to-share clips. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
就緒
$0.56每次運行·~17 / $10
Golden hour shot. A young woman with curly hair walking in a field of tall grass turns back to look at the camera and smiles genuinely. The low sun is behind her, creating a beautiful rim light (backlight) on her hair. Dust motes dancing in the light. Handheld camera feel, warm and nostalgic.
Kling V3.0 Pro is Kuaishou's premium text-to-video model, delivering the highest visual quality and motion realism in the V3.0 family. Describe any scene — the model generates cinematic video with superior detail, flexible duration from 3 to 15 seconds, multiple aspect ratios, and optional synchronized sound generation.
V3.0 Pro quality The highest visual fidelity and motion realism in the Kling V3.0 family.
Flexible duration Generate videos from 3 to 15 seconds — any length you need.
Aspect ratio control Multiple options including 16:9, 9:16, 1:1, and more to fit any platform.
Sound generation Optional synchronized sound effects generated alongside the video.
Negative prompt support Specify what you don't want in the video for more precise control.
Multi-prompt and element list support Chain prompt segments for scene transitions and lock in specific visual elements for consistency.
Prompt Enhancer Built-in tool to automatically improve your descriptions for better results.
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the desired scene, motion, camera style, and atmosphere. |
| negative_prompt | No | Elements to exclude from the video. |
| duration | No | Video length in seconds. Range: 3–15. Default: 5. |
| aspect_ratio | No | Video aspect ratio. Default: 16:9. |
| cfg_scale | No | Prompt guidance strength. Default: 0.5. |
| sound | No | Generate synchronized sound alongside the video. Default: disabled. |
| shot_type | No | Editing mode: intelligent (default, auto-determines scope) or customize. |
| multi_prompt | No | Additional prompts for complex scene compositions. |
| element_list | No | List of visual elements to maintain consistency throughout the clip. |
| Duration | Without Sound | With Sound |
|---|---|---|
| 3s | $0.336 | $0.504 |
| 5s | $0.560 | $0.840 |
| 10s | $1.120 | $1.680 |
| 15s | $1.680 | $2.520 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-pro/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 Kling v3.0 Pro Text To Video below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-pro/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",
"negative_prompt": "blurry, low quality, distorted",
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"sound": false,
"shot_type": "customize"
}'
# 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("kwaivgi/kling-v3.0-pro/text-to-video", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"negative_prompt": "blurry, low quality, distorted",
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"sound": false,
"shot_type": "customize"
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"kwaivgi/kling-v3.0-pro/text-to-video",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"negative_prompt": "blurry, low quality, distorted",
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"sound": false,
"shot_type": "customize"
}
)
print(output["outputs"][0]) # → URL of the generated outputKling v3.0 Pro Text To Video is a Kuaishou model for video generation, exposed as a REST API on WaveSpeedAI. Kling 3.0 Pro delivers top-tier text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and native audio for ready-to-share clips. Ready-to-use REST inference API, best performance, no cold starts, 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/kwaivgi/kwaivgi-kling-v3.0-pro-text-to-video.
Kling v3.0 Pro Text To Video starts at $0.56 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`, `duration`, `negative_prompt`, `cfg_scale`, `element_list`. 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/kwaivgi/kwaivgi-kling-v3.0-pro-text-to-video.
Average end-to-end generation time on WaveSpeedAI is around 2370 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 (Kuaishou). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.