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Kling V3 Turbo Pro Image to Video API

kwaivgi /

Kling V3 Turbo Pro converts first-frame images and optional prompts into high quality 1080P videos with fast pro-tier inference and multi-shot storyboard support. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
입력

드래그 앤 드롭 또는 클릭하여 업로드

preview

대기 중

$0.14실행당·~71 / $10

다음:

예시전체 보기

Pages fly out from the shelves and spiral into the portal. The student reaches for one floating page, the library clock spins backward, and the camera rotates slightly as the room bends around him.

관련 모델

README

Kling V3 Turbo Pro Image-to-Video

Kling V3 Turbo Pro Image-to-Video generates high quality 1080p videos from a first-frame reference image. It supports optional text guidance and multi-shot storyboard generation.

Why Choose This?

  • First-frame image animation
    Turn a still image into a high quality video using the image as the starting frame.

  • High quality 1080p output
    Use the pro-tier model for stronger detail and visual quality.

  • Optional prompt guidance
    Add a prompt to guide motion, camera movement, and scene behavior.

  • Multi-shot storyboard support
    Use multi_prompt to define multiple prompted segments with separate durations.

  • Standard video output
    The generated video is returned as a URL in the standard WaveSpeed prediction response.

Parameters

ParameterRequiredDescription
imageYesFirst-frame reference image URL. JPG and PNG images work best.
promptNoOptional text prompt to guide the generated video. Mutually exclusive with multi_prompt.
multi_promptNoMulti-shot storyboard. Each item includes a prompt and duration. Mutually exclusive with prompt.
durationNoVideo duration in seconds for single-prompt generation. Options: 3 to 15. Default: 5.

How to Use

  1. Upload an image — Provide the first-frame reference image.
  2. Enter a prompt (optional) — Describe the desired motion, camera movement, or scene change.
  3. Or create a storyboard — Use multi_prompt to define multiple prompted segments.
  4. Set duration — Choose the video duration for single-prompt generation, or set durations per shot in multi_prompt.
  5. Submit — Generate the animated video output.

Output

Returns generated video URL(s) in the standard WaveSpeed prediction response.

The generated video is returned as MP4 video.

Pricing

Pricing is $0.14 per second.

WaveSpeed bills by the generated video duration. If multi_prompt is provided, billing uses the selected duration plus the sum of all segment durations.

Generated DurationPrice
3s$0.42
5s$0.70
10s$1.40
15s$2.10

Billing Rules

  • Billing is based on generated video duration.
  • Single-prompt requests use the duration parameter.
  • multi_prompt requests use duration plus the sum of all segment durations.
  • Each second costs $0.14.

Best Use Cases

  • Image animation — Animate still images into short video clips.
  • Product motion concepts — Create motion previews from product or object images.
  • Character and scene animation — Add movement to portraits, scenes, or illustrated frames.
  • Storyboard generation — Build multi-shot videos from one starting image.
  • Creative video prototyping — Quickly test image-driven video directions.

Pro Tips

  • Use a sharp, high quality image with a clear subject.
  • Add motion and camera details in the prompt for stronger control.
  • Use multi_prompt when you want multiple guided segments.
  • Keep total multi_prompt duration within the model limit.
  • Make sure the image URL is publicly accessible.

Notes

  • image is required.
  • prompt is optional.
  • prompt and multi_prompt are mutually exclusive.
  • duration is used for single-prompt generation.
  • multi_prompt supports per-shot durations.
  • The total generated duration must not exceed 15 seconds.
참고:이 웹사이트는 제3자가 제공하는 AI 모델을 사용합니다.

Kling v3 Turbo Pro Image To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3-turbo-pro/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 Turbo Pro 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"
}
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-turbo-pro/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-turbo-pro/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "duration": "5"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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"
}

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-turbo-pro/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 Turbo Pro Image To Video API — Frequently asked questions

What is the Kling v3 Turbo Pro Image To Video API?

Kling v3 Turbo Pro Image To Video is a Kuaishou model for video generation from images, exposed as a REST API on WaveSpeedAI. Kling V3 Turbo Pro converts first-frame images and optional prompts into high quality 1080P videos with fast pro-tier inference and multi-shot storyboard support. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Kling v3 Turbo Pro 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-turbo-pro-image-to-video.

How much does Kling v3 Turbo Pro Image To Video cost per run?

Kling v3 Turbo Pro Image To Video starts at $0.14 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 Turbo Pro Image To Video accept?

Key inputs: `prompt`, `image`, `duration`, `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-turbo-pro-image-to-video.

How long does Kling v3 Turbo Pro Image To Video take to generate?

Average end-to-end generation time on WaveSpeedAI is around 213 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Kling v3 Turbo Pro 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 Turbo Pro Image to Video API | WaveSpeedAI