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Home/Models/Kling/Kling Video
K

Kling Video

Per Request:$0.13216
Video Generation
Commercial Use
Overview
Features
Pricing
API

Technical Specifications of kling_video

SpecificationDetails
Model IDkling_video
CategoryVideo Generation
Primary CapabilityGenerates videos from text prompts and, depending on workflow, can support image-guided video creation
Input TypesText prompts, and in some implementations image inputs for image-to-video workflows
Output TypeAI-generated video
Common Use CasesShort-form creative clips, cinematic concept visualization, marketing content, social media assets, animation prototyping
StrengthsStrong motion quality, visual aesthetics, and prompt adherence
Integration PatternAPI-based request/response workflow through CometAPI
Best ForDevelopers and teams building automated video generation features into apps, tools, and content pipelines

What is kling_video?

kling_video is CometAPI’s platform model identifier for accessing a video generation model designed to create AI-generated videos from natural language instructions. It is suitable for users who want to turn descriptive prompts into visually dynamic clips for creative production, prototyping, storytelling, and media workflows.

This model is especially useful for applications that need automated video generation as part of a broader product experience. Developers can use kling_video to power features such as prompt-to-video creation, concept visualization, ad creative generation, and experimental media tooling, all through a standard API integration flow.

Main features of kling_video

  • Text-to-video generation: Create videos directly from natural language prompts describing scenes, motion, style, subjects, and atmosphere.
  • Image-guided generation support: In compatible workflows, use reference images to help steer composition, character appearance, or scene structure.
  • High-quality motion synthesis: Well-suited for generating clips with more fluid movement and stronger visual continuity than basic animation pipelines.
  • Strong prompt adherence: Designed to follow user instructions closely, making it useful for controlled creative generation.
  • Aesthetic visual output: Helpful for cinematic concepts, polished short clips, and visually engaging marketing or social assets.
  • Creative workflow automation: Can be embedded into applications that need repeatable video generation without manual editing steps.
  • API-friendly deployment: Accessible through CometAPI using a consistent developer integration pattern that fits existing AI application stacks.

How to access and integrate

Step 1: Sign Up for API Key

First, register for a CometAPI account and generate your API key from the dashboard. This key is required to authenticate all requests. Store it securely in your server environment and avoid exposing it in client-side code.

Step 2: Send Requests to kling_video API

Use CometAPI's Kling-compatible endpoint. For video generation, send a POST request to /kling/v1/videos/text2video (or /kling/v1/videos/image2video for image-to-video).

curl https://api.cometapi.com/kling/v1/videos/text2video \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_API_KEY" \
  -d '{
    "prompt": "A cinematic scene with dramatic lighting.",
    "model_name": "kling-v2-master",
    "aspect_ratio": "16:9",
    "duration": "5"
  }'

Step 3: Retrieve and Verify Results

The API returns a task ID. Poll GET /kling/v1/videos/text2video/{task_id} to check generation status and retrieve the output video URL when complete.

Features for Kling Video

Explore the key features of Kling Video , designed to enhance performance and usability. Discover how these capabilities can benefit your projects and improve user experience.

Pricing for Kling Video

Explore competitive pricing for Kling Video , designed to fit various budgets and usage needs. Our flexible plans ensure you only pay for what you use, making it easy to scale as your requirements grow. Discover how Kling Video can enhance your projects while keeping costs manageable.
VersionQualityDurationPrice
v1std5s$0.13
v1std10s$0.26
v1pro5s$0.46
v1pro10s$0.92
v1.5/v1.6std5s$0.26
v1.5/v1.6std10s$0.53
v1.5/v1.6pro5s$0.46
v1.5/v1.6pro10s$0.92
v2-master-5s$1.32
v2-master-10s$2.64
v2-1std5s$0.26
v2-1std10s$0.53
v2-1pro5s$0.46
v2-1pro10s$0.92
v2-1-master-5s$1.32
v2-1-master-10s$2.64
v2-5-turbopro5s$0.33
v2-5-turbopro10s$0.66
v2-6 (no native audio)pro5s$0.33
v2-6 (no native audio)pro10s$0.67
v2-6 (native audio, no voice control)pro5s$0.67
v2-6 (native audio, no voice control)pro10s$1.33
v2-6 (native audio, with voice control)pro5s$0.80
v2-6 (native audio, with voice control)pro10s$1.60

Sample code and API for Kling Video

Access comprehensive sample code and API resources for Kling Video to streamline your integration process. Our detailed documentation provides step-by-step guidance, helping you leverage the full potential of Kling Video in your projects.
Python
JavaScript
Curl
import requests
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/kling/v1"

headers = {
    "Authorization": f"Bearer {COMETAPI_KEY}",
    "Content-Type": "application/json",
}

# ============================================================
# Step 1: Create Video Task
# ============================================================
print("Step 1: Creating video task...")

create_payload = {
    "prompt": "A happy scene of a vacation on the beach.",
    "model_name": "kling-v2-6",
}

create_response = requests.post(
    f"{BASE_URL}/videos/text2video", headers=headers, json=create_payload
)

create_result = create_response.json()
print(f"Create response: {create_result}")

# Extract task ID from the response
task_id = create_result.get("data", {}).get("task_id")
if not task_id:
    print("Error: Failed to get task_id from response")
    exit(1)

print(f"Task ID: {task_id}")

# ============================================================
# Step 2: Query Task Status
# ============================================================
print("
Step 2: Querying task status...")

query_response = requests.get(
    f"{BASE_URL}/videos/text2video/{task_id}", headers=headers
)

query_result = query_response.json()
print(f"Query response: {query_result}")

# Check task status
task_status = query_result.get("data", {}).get("status") or query_result.get(
    "data", {}
).get("task_status")
print(f"Task status: {task_status}")

Python Code Example

import requests
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/kling/v1"

headers = {
    "Authorization": f"Bearer {COMETAPI_KEY}",
    "Content-Type": "application/json",
}

# ============================================================
# Step 1: Create Video Task
# ============================================================
print("Step 1: Creating video task...")

create_payload = {
    "prompt": "A happy scene of a vacation on the beach.",
    "model_name": "kling-v2-6",
}

create_response = requests.post(
    f"{BASE_URL}/videos/text2video", headers=headers, json=create_payload
)

create_result = create_response.json()
print(f"Create response: {create_result}")

# Extract task ID from the response
task_id = create_result.get("data", {}).get("task_id")
if not task_id:
    print("Error: Failed to get task_id from response")
    exit(1)

print(f"Task ID: {task_id}")

# ============================================================
# Step 2: Query Task Status
# ============================================================
print("\nStep 2: Querying task status...")

query_response = requests.get(
    f"{BASE_URL}/videos/text2video/{task_id}", headers=headers
)

query_result = query_response.json()
print(f"Query response: {query_result}")

# Check task status
task_status = query_result.get("data", {}).get("status") or query_result.get(
    "data", {}
).get("task_status")
print(f"Task status: {task_status}")

JavaScript Code Example

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const base_url = "https://api.cometapi.com/kling/v1";

const headers = {
  "Authorization": `Bearer ${api_key}`,
  "Content-Type": "application/json",
};

async function main() {
  // ============================================================
  // Step 1: Create Video Task
  // ============================================================
  console.log("Step 1: Creating video task...");

  const createPayload = {
    prompt: "A happy scene of a vacation on the beach.",
    model_name: "kling-v2-6"
  };

  const createResponse = await fetch(`${base_url}/videos/text2video`, {
    method: "POST",
    headers: headers,
    body: JSON.stringify(createPayload)
  });

  const createResult = await createResponse.json();
  console.log("Create response:", JSON.stringify(createResult, null, 2));

  // Extract task ID from the response
  const taskId = createResult?.data?.task_id;
  if (!taskId) {
    console.log("Error: Failed to get task_id from response");
    process.exit(1);
  }

  console.log(`Task ID: ${taskId}`);

  // ============================================================
  // Step 2: Query Task Status
  // ============================================================
  console.log("\nStep 2: Querying task status...");

  const queryResponse = await fetch(`${base_url}/videos/text2video/${taskId}`, {
    method: "GET",
    headers: headers
  });

  const queryResult = await queryResponse.json();
  console.log("Query response:", JSON.stringify(queryResult, null, 2));

  // Check task status
  const taskStatus = queryResult?.data?.status || queryResult?.data?.task_status;
  console.log(`Task status: ${taskStatus}`);
}

main();

Curl Code Example

#!/bin/bash

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

BASE_URL="https://api.cometapi.com/kling/v1"

# ============================================================
# Step 1: Create Video Task
# ============================================================
echo "Step 1: Creating video task..."

CREATE_RESPONSE=$(curl -s --location --request POST "${BASE_URL}/videos/text2video" \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "Content-Type: application/json" \
  --data-raw '{
    "prompt": "A happy scene of a vacation on the beach.",
    "model_name": "kling-v2-6"
  }')

echo "Create response: $CREATE_RESPONSE"

# Extract task_id using jq (install with: brew install jq)
TASK_ID=$(echo "$CREATE_RESPONSE" | jq -r '.data.task_id')

if [ "$TASK_ID" == "null" ] || [ -z "$TASK_ID" ]; then
  echo "Error: Failed to get task_id from response"
  exit 1
fi

echo "Task ID: $TASK_ID"

# ============================================================
# Step 2: Query Task Status
# ============================================================
echo ""
echo "Step 2: Querying task status..."

QUERY_RESPONSE=$(curl -s --location --request GET "${BASE_URL}/videos/text2video/${TASK_ID}" \
  --header "Authorization: Bearer $COMETAPI_KEY")

echo "Query response:"
echo "$QUERY_RESPONSE" | jq .

# Check task status
TASK_STATUS=$(echo "$QUERY_RESPONSE" | jq -r '.data.status // .data.task_status')
echo "Task status: $TASK_STATUS"

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