Kling V3.0 4K delivers top-tier 4K text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and optional audio. Supports flexible aspect ratios, multi-prompt, and element references. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
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A cyberpunk street at night in heavy rain, neon signs flickering. Crowds with umbrellas walking through reflections on wet asphalt. Camera slowly dolly forward at eye level. Lighting: neon glow, reflections, volumetric fog. Style: Blade Runner aesthetic, ultra-detailed, cinematic. Rain particles, holographic ads flickering. 4K, 24fps, slow motion feel.
A soft anime-style girl standing in a field. Hair gently flowing in the wind, blinking slowly. Camera: static close-up, slight breathing motion. Lighting: warm sunset glow. Style: Studio Ghibli inspired, soft shading. Loopable animation, seamless. 6s, smooth loop.
Kling V3.0 4K is Kuaishou's premium text-to-video model, delivering 4K cinematic video generation from natural language prompts. Supports flexible duration from 3 to 15 seconds, multiple aspect ratios, optional synchronized sound, and multi-prompt scene transitions.
4K quality
The highest visual fidelity and motion realism in the Kling V3.0 family.
Flexible duration
Generate videos from 3 to 15 seconds.
Aspect ratio control
Multiple options including 16:9, 9:16, and 1:1.
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 support
Chain prompt segments to guide scene transitions and complex scene compositions.
| Parameter | Required | Description |
|---|---|---|
| prompt | No | 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: 16:9 default, 9:16, 1:1. |
| cfg_scale | No | Prompt guidance strength. Range: 0–1. Default: 0.5. |
| sound | No | Generate synchronized sound alongside the video. Default: disabled. |
| shot_type | No | Editing mode: customize default or intelligent. |
| multi_prompt | No | Additional prompts for complex scene compositions. |
$0.42 per second of video, regardless of whether audio is on or off.
| Duration | Cost |
|---|---|
| 3s | $1.26 |
| 5s | $2.10 |
| 10s | $4.20 |
| 15s | $6.30 |
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-4k/text-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Kling v3.0 4k Text To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"shot_type": "customize"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-4k/text-to-video" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-4k/text-to-video";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"shot_type": "customize"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"duration": 5,
"aspect_ratio": "16:9",
"cfg_scale": 0.5,
"shot_type": "customize"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-4k/text-to-video", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Kling v3.0 4k Text To Video is a Kuaishou model for video generation, exposed as a REST API on WaveSpeedAI. Kling V3.0 4K delivers top-tier 4K text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and optional audio. Supports flexible aspect ratios, multi-prompt, and element references. 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 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/kwaivgi/kwaivgi-kling-v3.0-4k-text-to-video.
Kling v3.0 4k Text To Video starts at $2.10 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`, `aspect_ratio`, `duration`, `negative_prompt`, `cfg_scale`, `multi_prompt`. 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-v3.0-4k-text-to-video.
Median end-to-end generation time on WaveSpeedAI is around 150 seconds per request, based on recent successful runs. Queue time varies 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.