Name: Kling Avatar Standard API
Brand: Kling AI

Overview

What is Kling Avatar Standard API?

Kling Avatar creates dynamic videos from avatar reference images with audio synchronization using standard mode for cost-effective generation.

Technical Specifications
- Supported inputs: Image
- Output: Video

Performance Benchmarks
[embed]

Kling Avatar Standard API Pricing
- Pricing on request

Where to Use Kling Avatar Standard

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

An exact-source result for Kling Avatar Standard only explicitly documents it as generating expressive character animations from a single image and a voice track, aligned to speech rhythm, intonation, and meaning. It is also documented as taking an avatar image plus speech content to generate an avatar video, with optional avatar prompting.

A second documented use is course and knowledge explainers, where the model is used with course audio and a fixed character image to test avatar flow, lip sync, pauses, identity consistency, and rights before publishing.

A third documented use is product narration samples, where it creates short product-audio comparison clips for evaluating output and cost against a human presenter, captions, or another avatar model.

A fourth documented use is support and notification clips, including splitting longer explainers, training material, or branded avatar narration into authorized segments before submission.

How to use Kling Avatar Standard API

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

import requests, time

headers = {"Authorization": "Bearer " + AIMLAPI_KEY}
job = requests.post(
    "https://api.aimlapi.com/v2/video/generations",
    headers=headers,
    json={
      "model": "klingai/avatar-standard",
      "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/avatar-standard",
    "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/avatar-standard","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.