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Kling V3 Turbo Standard Text to Video API

kwaivgi /

Kling V3 Turbo Standard is a fast text-to-video model that generates 720P videos from text prompts, supports single-prompt generation, and can create multi-shot storyboard videos. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-video
Input

Idle

$0.112per run·~89 / $10

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ExamplesView all

An elderly foreign couple dancing in an empty vintage ballroom, dusty sunlight through tall windows, old wooden floor, elegant clothing, emotional cinematic realism

Related Models

README

Kling V3 Turbo Standard Text-to-Video

Kling V3 Turbo Standard Text-to-Video generates fast, affordable 720p videos from text prompts. It supports both single-prompt generation and multi-shot storyboard generation with per-shot durations.

Why Choose This?

  • Fast 720p video generation
    Create efficient standard-tier videos directly from text prompts.

  • Lower cost generation
    Use the standard model for affordable video creation and iteration.

  • Single prompt or multi-shot storyboard
    Generate a complete video from one prompt, or use multi_prompt to define multiple shots.

  • Per-shot duration control
    Set each storyboard segment duration when using multi_prompt.

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

Parameters

ParameterRequiredDescription
promptNoText prompt describing the video to generate. Mutually exclusive with multi_prompt.
multi_promptNoMulti-shot storyboard. Each item includes a prompt and duration. Mutually exclusive with prompt.
aspect_ratioNoOutput aspect ratio. Options: 16:9, 9:16, 1:1. Default: 16:9.
durationNoVideo duration in seconds for single-prompt generation. Options: 3 to 15. Default: 5.

How to Use

  1. Enter a prompt — Describe the scene, subject, motion, and style you want.
  2. Or create a storyboard — Use multi_prompt to define multiple shots with individual durations.
  3. Choose aspect ratio — Select 16:9, 9:16, or 1:1.
  4. Set duration — Choose the video duration for single-prompt generation, or set durations per shot in multi_prompt.
  5. Submit — Generate the 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 $0.112 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$0.336
5s$0.56
10s$1.12
15s$1.68

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 $0.112.

Best Use Cases

  • Fast text-to-video creation — Turn written ideas into short video clips.
  • Affordable iteration — Test multiple prompt directions at lower cost.
  • Storyboard generation — Build multi-shot videos with separate prompts per segment.
  • Social video drafts — Prototype short clips for posts, ads, or concepts.
  • Creative exploration — Try different motions, scenes, and camera directions.

Pro Tips

  • Use clear subject, action, camera, and style details in the prompt.
  • Use multi_prompt when you need multiple shots instead of one continuous prompt.
  • Keep total multi_prompt duration within the model limit.
  • Use consistent wording across storyboard segments for better visual continuity.
  • Choose the aspect ratio before writing composition-heavy prompts.

Notes

  • Provide either prompt or multi_prompt.
  • 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.
नोट:This website uses AI models provided by third parties.

Kling v3 Turbo Std Text To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3-turbo-std/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 Turbo Std Text To Video below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "aspect_ratio": "16:9",
    "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-std/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-turbo-std/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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "aspect_ratio": "16:9",
        "duration": "5"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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 = {
    "aspect_ratio": "16:9",
    "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-std/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 Turbo Std Text To Video API — Frequently asked questions

What is the Kling v3 Turbo Std Text To Video API?

Kling v3 Turbo Std Text To Video is a Kuaishou model for video generation, exposed as a REST API on WaveSpeedAI. Kling V3 Turbo Standard is a fast text-to-video model that generates 720P videos from text prompts, supports single-prompt generation, and can create multi-shot storyboard videos. 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 Std 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-turbo-std-text-to-video.

How much does Kling v3 Turbo Std Text To Video cost per run?

Kling v3 Turbo Std Text To Video starts at $0.11 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 Std Text To Video accept?

Key inputs: `prompt`, `aspect_ratio`, `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-std-text-to-video.

How long does Kling v3 Turbo Std Text To Video take to generate?

Average end-to-end generation time on WaveSpeedAI is around 89 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 Std 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 Turbo Standard Text to Video API | WaveSpeedAI