MiniMax H3 オープンウェイト | 動画ジェネレーターで試す →

Kling V3.0 Std Text to Video | Powerful Text-to-Video

kwaivgi/

Kling 3.0 Standard delivers high-quality text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and native audio for ready-to-share clips. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

text-to-video
入力

待機中

$0.421回あたり·~23 / $10

次:

サンプルすべて表示

Wide-angle shot. A lone figure with a large backpack walking through a dust storm-swept post-apocalyptic desert ruin. Wind blowing their cloak. Slow camera dolly out to reveal the desolate environment. Grainy film look.

A young woman with long curly brown hair sits in a dark movie theater on a deep red velvet seat, holding a red paper cup in both hands. She gazes up at the screen with a soft, amused smile. Her expression shifts subtly — her eyes widen slightly with interest, then she lets out a gentle laugh, her shoulders rising briefly. Her curly hair sways ever so slightly as she tilts her head. The flickering light from the movie screen casts warm, shifting reflections across her face, alternating between soft highlights and shadow. She lifts the red cup slowly to take a sip, then lowers it back down. The dark cinema background with rows of empty red seats remains still and moody. Cinematic lighting, shallow depth of field, warm color grading. 4K, 24fps.

関連モデル

README

Kling V3.0 Std Text-to-Video

Kling V3.0 Standard Text-to-Video is Kuaishou's cost-efficient text-to-video model, generating smooth, cinematic video directly from natural language prompts at accessible pricing. With flexible duration, multiple aspect ratios, optional synchronized sound, and precise prompt control, it delivers strong visual quality for a wide range of production workflows.

Why Choose This?

  • V3.0 quality at Standard pricing
    Strong visual quality and motion coherence at a fraction of Pro tier cost.

  • Flexible duration
    Generate videos from 3 to 15 seconds to match your scene needs.

  • Multiple aspect ratios
    Support for 16:9, 9:16, and 1:1 to fit any platform or format.

  • 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 over the output.

  • Multi-prompt support
    Chain prompt segments to guide scene transitions and progression.

  • Prompt Enhancer
    Built-in tool to automatically improve your video descriptions.

Parameters

ParameterRequiredDescription
promptNoText description of the scene, motion, camera style, and atmosphere.
negative_promptNoElements to exclude from the video.
durationNoVideo length in seconds. Range: 3–15. Default: 5.
aspect_ratioNoOutput ratio: 16:9 (default), 9:16, 1:1.
cfg_scaleNoPrompt guidance strength. Default: 0.5.
soundNoGenerate synchronized sound alongside the video. Default: disabled.
shot_typeNoEditing mode: intelligent (default, auto-determines scope) or customize.
multi_promptNoAdditional prompt segments to guide scene transitions and progressions.

How to Use

  1. Write your prompt — describe the scene, characters, camera movement, lighting, and atmosphere. Use the Prompt Enhancer for better results.
  2. Add negative prompt (optional) — specify elements you want to exclude from the output.
  3. Set duration — choose any length from 3 to 15 seconds.
  4. Select aspect ratio — 16:9 for landscape, 9:16 for portrait/social, 1:1 for square.
  5. Adjust cfg_scale (optional) — increase for stricter prompt adherence, decrease for more creative variation.
  6. Enable sound (optional) — generate synchronized audio alongside the video.
  7. Select shot_type (optional) — use intelligent for automatic scope, or customize for manual control.
  8. Add multi-prompt segments (optional) — click Add Item to guide scene transitions.
  9. Run — submit and download your video.

Pricing

DurationWithout SoundWith Sound
3s$0.252$0.378
5s$0.420$0.630
10s$0.840$1.260
15s$1.260$1.890

Billing Rules

  • Base rate: $0.42 per 5 seconds ($0.084 per second)
  • Sound surcharge: ×1.5 when sound is enabled
  • Duration range: 3–15 seconds

Best Use Cases

  • Social Media Content — Generate portrait or square clips for TikTok, Reels, and Shorts at scale.
  • Concept Visualization — Quickly bring creative ideas and moods to life from text descriptions.
  • Marketing & Advertising — Produce promotional video content without a film crew.
  • Prototyping — Test visual ideas and prompt variations at Standard pricing before committing to Pro.
  • Storytelling — Build narrative scenes from detailed text descriptions with consistent motion.

Pro Tips

  • The more specific your prompt, the better — include camera angle, lighting style, character behavior, and atmosphere.
  • Use negative_prompt to avoid common artifacts like blurry faces, unwanted motion, or specific visual elements.
  • Match aspect ratio to your platform: 16:9 for YouTube, 9:16 for TikTok and Reels, 1:1 for Instagram.
  • Enable sound for scenes with ambient environments, crowds, or action for a more immersive result.
  • Use shorter durations (3–5s) for rapid iteration, longer (10–15s) for final output.

Notes

  • All parameters are optional.
  • Duration range: minimum 3 seconds, maximum 15 seconds.
  • Sound generation increases cost by 1.5×.

Related Models

注記:本サイトは第三者が提供するAIモデルを使用しています。

Kling v3.0 Std Text To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v3.0-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 v3.0 Std 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-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-v3.0-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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "duration": 5,
        "aspect_ratio": "16:9",
        "cfg_scale": 0.5,
        "shot_type": "customize"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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-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 v3.0 Std Text To Video API — Frequently asked questions

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

Kling v3.0 Std Text To Video is a Kuaishou model for video generation, exposed as a REST API on WaveSpeedAI. Kling 3.0 Standard delivers high-quality text-to-video generation with smooth motion, cinematic visuals, accurate prompt adherence, and native audio for ready-to-share clips. 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 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-v3.0-std-text-to-video.

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

Kling v3.0 Std Text To Video starts at $0.42 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 Std 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-std-text-to-video.

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

Median end-to-end generation time on WaveSpeedAI is around 88 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 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 V3.0 Std Text to Video | Powerful Text-to-Video API on WaveSpeedAI