Seedream 5.0 Pro is LIVE | Try in Image Generator →

Kling V2 AI Avatar Standard

kwaivgi /

Kling AI Avatar generates high-quality AI avatar videos for profiles, intros, and social content, delivering clean detail and cinematic motion with reliable prompt adherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

digital-human
Input

Idle

$0.28per run·~35 / $10

ExamplesView all

Related Models

README

Kling V2 AI Avatar Standard

What is Kling V2 AI Avatar Standard?

Kling V2 AI Avatar Standard turns a single image + one audio track into a realistic talking-avatar video. It’s built on the Kling V2 avatar stack, combining precise lip sync, rich facial expressions, and smooth head motion to create natural digital presenters for intros, explainers, tutorials, and more.

It works with human portraits, stylized characters, or even pets, animating them to speak or sing while keeping their visual identity consistent across the entire clip.

Why it looks great

  • Accurate lip synchronization: Aligns mouth shapes and jaw movement tightly with the audio, preserving rhythm, pronunciation, and timing even for fast speech.

  • Expressive face & head motion: Goes beyond lip movement to animate head turns, eye blinks, eyebrow motion, and micro-expressions that follow the emotion of the voice.

  • Identity preservation: Maintains consistent facial identity, hairstyle, and overall visual style from frame to frame, so the avatar always looks like the source image.

  • Image-to-video capability: Turns static photos or character art into lively speaking or singing videos, adapting motion to realistic or stylized input images.

  • Instruction following: Accepts optional text prompts to control mood, energy, and behavior (e.g., “calm news anchor” vs “high-energy streamer”), while still syncing to the audio.

Pricing

Billing is based on audio duration, with a minimum of 5 seconds.

Audio length (s)Billed secondsPrice (USD)
0–550.28
10100.56

Any clip shorter than 5 seconds is still billed as 5 seconds.

Billing Rules

  • Minimum Charge: All videos are billed for a minimum of 5 seconds (at least $0.15)
  • Billing Cap: Billing is capped at 300 seconds (5 minutes) per job.

How to Use

  1. Upload the audio file
  • Use a clean voice track (recorded or TTS).
  • Trim long silences at the beginning and end.
  1. Upload the image
  • A clear portrait or character image works best (front or slight 3/4 view).
  • Real people, stylized characters, or animals are all supported.
  1. (Optional) Add a prompt
  • Describe the style and behavior, e.g.
  • “friendly teacher, gentle head nods”
  • “excited host, big smiles and energetic motion”
  1. Submit the job and download the result
  • Create the task, wait for processing to finish, then download or stream the generated video.

Note

  • Max clip length per job: up to 5 minutes (or your configured backend limit).
  • Typical performance: longer and higher-resolution clips take more time to render.
  • Input tips:
  • Use high-resolution, well-lit images without heavy filters.
  • Avoid large occlusions (hands, masks, big sunglasses) around the mouth.

More Versions

  • Kling V2 AI Avatar Pro Advanced AI avatar generation for short-form video and social content, optimized for expressive faces, lip sync, and character-driven clips.

  • Infinite Talk Real-time conversational AI voice experience, ideal for interactive agents, roleplay characters, and always-on voice companions.

Reference

Note:This website uses AI models provided by third parties.

Kling v2 Ai Avatar Standard API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2-ai-avatar-standard 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 v2 Ai Avatar Standard 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",
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2-ai-avatar-standard" \
  -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-v2-ai-avatar-standard";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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",
    "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3"
}

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-v2-ai-avatar-standard", 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 v2 Ai Avatar Standard API — Frequently asked questions

What is the Kling v2 Ai Avatar Standard API?

Kling v2 Ai Avatar Standard is a Kuaishou model for talking-avatar generation, exposed as a REST API on WaveSpeedAI. Kling AI Avatar generates high-quality AI avatar videos for profiles, intros, and social content, delivering clean detail and cinematic motion with reliable prompt adherence. 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 v2 Ai Avatar Standard 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-v2-ai-avatar-standard.

How much does Kling v2 Ai Avatar Standard cost per run?

Kling v2 Ai Avatar Standard starts at $0.28 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 v2 Ai Avatar Standard accept?

Key inputs: `prompt`, `image`, `audio`. 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-v2-ai-avatar-standard.

How long does Kling v2 Ai Avatar Standard take to generate?

Median end-to-end generation time on WaveSpeedAI is around 264 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 v2 Ai Avatar Standard 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.