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Kling V3.0 4K Text to Video

kwaivgi /

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.

text-to-video
입력

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$2.1실행당

다음:

예시전체 보기

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.

관련 모델

README

Kling V3.0 4K Text-to-Video

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.

Why Choose This?

  • 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.

Parameters

ParameterRequiredDescription
promptNoText description of the desired scene, motion, camera style, and atmosphere.
negative_promptNoElements to exclude from the video.
durationNoVideo length in seconds. Range: 3–15. Default: 5.
aspect_ratioNoVideo aspect ratio: 16:9 default, 9:16, 1:1.
cfg_scaleNoPrompt guidance strength. Range: 0–1. Default: 0.5.
soundNoGenerate synchronized sound alongside the video. Default: disabled.
shot_typeNoEditing mode: customize default or intelligent.
multi_promptNoAdditional prompts for complex scene compositions.

How to Use

  1. Write your prompt — Describe the scene, motion, camera movement, and mood in detail.
  2. Add negative prompt optional — Specify elements you want to exclude.
  3. Set duration — Choose any length from 3 to 15 seconds.
  4. Choose aspect ratio — Select the format that fits your platform.
  5. Adjust cfg_scale optional — Control how closely the output follows your prompt.
  6. Enable sound optional — Generate synchronized audio alongside the video.
  7. Add multi-prompt segments optional — Use additional prompt segments for more complex scene progression.
  8. Submit — Generate, preview, and download your video.

Pricing

$0.42 per second of video, regardless of whether audio is on or off.

DurationCost
3s$1.26
5s$2.10
10s$4.20
15s$6.30

Best Use Cases

  • Premium Production — Cinematic scenes requiring the highest visual quality in 4K.
  • Marketing & Ads — High-end promotional videos with professional polish.
  • Film & Storytelling — Film-quality scenes with superior motion and detail.
  • Brand Content — Premium video content for brands demanding top-tier visuals.

Pro Tips

  • Use detailed, cinematic prompts — include lighting, camera angles, and motion descriptions.
  • Use negative_prompt to avoid common issues like blurry faces or unwanted elements.
  • Enable sound for environmental audio like rain, city ambience, or action effects.
  • Match aspect ratio to your target platform: 16:9 for YouTube, 9:16 for TikTok, 1:1 for feeds.
  • Use multi_prompt when you need more complex scene progression or transitions.

Related Models

참고:이 웹사이트는 제3자가 제공하는 AI 모델을 사용합니다.

Kling v3.0 4k Text To Video API — Quick start

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.

HTTP example
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
done
Node.js example
const 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));
}
Python example
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 API — Frequently asked questions

What is the Kling v3.0 4k Text To Video API?

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.

How do I call the Kling v3.0 4k Text To Video API?

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.

How much does Kling v3.0 4k Text To Video cost per run?

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.

What inputs does Kling v3.0 4k Text To Video accept?

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.

How long does Kling v3.0 4k Text To Video take to generate?

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.

Can I use Kling v3.0 4k Text To Video outputs commercially?

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.

Kling V3.0 4K Text to Video | Powerful Text-to-Video API | WaveSpeedAI