Name: Kling 3.0 Standard Turbo Text to Video API
Brand: Kling AI

Overview

What is Kling 3.0 Standard Turbo Text to Video API?

Kling 3.0 Turbo Standard text-to-video turns prompts into fast, cost-efficient 720p videos with native audio.

Technical Specifications
- Supported inputs: Text
- Output: Video

Performance Benchmarks
[embed]

Kling 3.0 Standard Turbo Text to Video API Pricing
- Pricing on request

Where to Use Kling 3.0 Standard Turbo Text to Video

Short-form video generation
Create clips for social, ads, and product demos from text or image prompts.

Previsualization and storyboards
Rapidly prototype motion concepts before committing to production.

Use cases

Turn prompts into short video clips for rapid idea testing and previewing motion styles. It is documented as suited to rapid iteration and high-volume production of video from text prompts.

Use it for directed shots and storyboard-style generation where cameras, scenes, and motion are described in the prompt. The documentation also frames it as a fit for professional storyboarding.

Use it for dynamic marketing content from text prompts. The cited material specifically names marketing as a good fit for this model.

Use it for social media storytelling and similar short-form video content. The documentation also lists social media storytelling as a suitable use case.

How to use Kling 3.0 Standard Turbo Text to Video API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to klingai/video-v3-standard-turbo-text-to-video.

import requests, time

headers = {"Authorization": "Bearer " + AIMLAPI_KEY}
job = requests.post(
    "https://api.aimlapi.com/v2/video/generations",
    headers=headers,
    json={
      "model": "klingai/video-v3-standard-turbo-text-to-video",
      "prompt": "A serene timelapse of clouds over a mountain range"
    },
).json()
gid = job["id"]

while True:
    res = requests.get(f"https://api.aimlapi.com/v2/video/generations?generation_id={gid}", headers=headers).json()
    if res.get("status") in ("completed", "error"):
        break
    time.sleep(5)
print(res["video"]["url"])

const headers = {
  Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
  "Content-Type": "application/json",
};
const job = await (await fetch("https://api.aimlapi.com/v2/video/generations", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "model": "klingai/video-v3-standard-turbo-text-to-video",
    "prompt": "A serene timelapse of clouds over a mountain range"
  }),
})).json();

let res;
do {
  await new Promise((r) => setTimeout(r, 5000));
  res = await (await fetch(`https://api.aimlapi.com/v2/video/generations?generation_id=${job.id}`, { headers })).json();
} while (!["completed", "error"].includes(res.status));
console.log(res.video.url);

# submit the generation — the response contains the job "id"
curl -X POST https://api.aimlapi.com/v2/video/generations \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"klingai/video-v3-standard-turbo-text-to-video","prompt":"A serene timelapse of clouds over a mountain range"}'

# then poll until status is "completed" — video.url holds the result
curl "https://api.aimlapi.com/v2/video/generations?generation_id={id}" -H "Authorization: Bearer $AIMLAPI_KEY"

OpenAI-compatible — swap the base URL and it works with your existing SDK.