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Kling V3.0 4K Image to Video

kwaivgi /

Kling V3.0 4K delivers top-tier 4K image-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and optional audio. Supports start/end frame control, multi-prompt, and element references. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

image-to-video
इनपुट

निष्क्रिय

$2.1प्रति रन

आगे:

उदाहरणसभी देखें

rain falling, slight breathing motion, subtle head movement camera slow dolly in neon reflections shimmering

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README

Kling V3.0 4K Image-to-Video

Kling V3.0 4K Image-to-Video is Kuaishou's premium image animation model delivering 4K output. Upload a reference image and describe the motion — the model generates cinematic video with superior detail, optional start-to-end frame guidance, and synchronized sound.

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.

  • Start-end frame guidance Optional end image for controlled transitions between two frames.

  • Sound generation Optional synchronized sound effects generated alongside the video.

  • Multi-prompt and element list support Chain prompt segments for scene transitions and lock in specific visual elements for consistency.

Parameters

ParameterRequiredDescription
imageYesStart frame image to animate (URL or upload).
promptNoText description of the desired motion and action.
negative_promptNoElements to exclude from the video.
end_imageNoEnd frame image for guided transitions.
durationNoVideo length in seconds (3-15, default: 5).
cfg_scaleNoPrompt guidance strength (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.
element_listNoList of visual elements to maintain consistency throughout the clip.

How to Use

  1. Upload your image — provide the reference image to animate.
  2. Write your prompt — describe the motion, camera movement, and action.
  3. Add negative prompt (optional) — specify elements to exclude.
  4. Upload end image (optional) — provide an end frame for guided transitions.
  5. Set duration — choose any length from 3 to 15 seconds.
  6. Enable sound (optional) — generate synchronized audio alongside the video.
  7. 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.
  • Scene Transitions — Use start and end frames for smooth cinematic transitions.
  • Marketing & Ads — High-end promotional videos with professional polish.
  • Character Animation — Animate portraits with superior motion and detail.

Pro Tips

  • Use detailed, cinematic prompts — include lighting, camera angles, and motion descriptions.
  • Add an end_image for controlled transitions between two visual states.
  • Use negative_prompt to avoid common issues like blurry faces or unwanted motion.
  • Enable sound for environmental audio like rain, city ambience, or action effects.
  • Use high-quality source images for the best video output.

Notes

  • Image is the only required field; all other parameters are optional.
  • Duration range: 3 to 15 seconds.
  • Audio does not affect pricing — $0.42 per second regardless.
  • Using element_list: First use Kling Elements to generate your element and note its name and ID. Then write the element name in your prompt and enter the element ID in the element_list field.
  • Ensure uploaded image URLs are publicly accessible.

Related Models

नोट:यह वेबसाइट तृतीय पक्षों द्वारा प्रदान किए गए AI मॉडलों का उपयोग करती है।

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

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-4k/image-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 Image To Video below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "duration": 5,
    "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/image-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/image-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "duration": 5,
        "cfg_scale": 0.5,
        "shot_type": "customize"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "duration": 5,
    "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/image-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 Image To Video API — Frequently asked questions

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

Kling v3.0 4k Image To Video is a Kuaishou model for video generation from images, exposed as a REST API on WaveSpeedAI. Kling V3.0 4K delivers top-tier 4K image-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and optional audio. Supports start/end frame control, 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 Image 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-image-to-video.

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

Kling v3.0 4k Image 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 Image To Video accept?

Key inputs: `prompt`, `image`, `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-v3.0-4k-image-to-video.

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

Median end-to-end generation time on WaveSpeedAI is around 169 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 Image 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 Image to Video | Fast Image-to-Video API | WaveSpeedAI