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Kling V2.1 T2V Master

kwaivgi /

Kling v2.1 creates cinematic 5-10s videos at 720p or 1080p from a single image or text prompt with improved motion fidelity and coherence. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

text-to-video
Input

Idle

$1.3per run

Next:

ExamplesView all

A close-up shot of an old fisherman with a weathered face and a twinkle in his eye, mending his fishing net. The background is a rustic wooden pier at sunrise. Soft golden hour light, photorealistic, 8K.

An epic wide shot of a futuristic city on Mars, featuring towering crystal skyscrapers, flying vehicles weaving through the air, and two red suns setting on the horizon. A sense of awe and wonder. Slow panning camera movement, sci-fi concept art style.

A majestic crystal dragon is soaring through a bioluminescent forest at night. Its scales shimmer with rainbow colors, leaving a trail of sparkling dust. The color palette is dominated by deep blues and vibrant purples. Fantasy art style, cinematic lighting.

An extreme close-up of a bee landing on a sunflower. We can see the fine hairs on the bee's body and the texture of the sunflower petals. A gentle breeze makes the sunflower sway slightly. The background is a soft-focus field of sunflowers under a clear blue sky. Hyperrealistic, shallow depth of field, bright daylight, slow motion (120fps).

An old man sits in a leather armchair by a window, a cup of steaming tea in his hands. He looks out the window with a nostalgic expression as rain streaks down the glass. The room is filled with warm, soft light from a nearby lamp. The focus is on his detailed, wrinkled face. Photorealistic, intimate portrait, moody lighting, sharp focus.

An overhead, macro shot of a chef's hands dusting a wooden board with flour. Fresh pasta dough is then rolled out with a wooden rolling pin. Flour particles dance in the air under a single spotlight. The focus is sharp on the texture of the dough and the grain of the wood. Hyperrealistic, food cinematography style, shallow depth of field, warm lighting.

A telephoto lens shot of a majestic snow leopard walking cautiously on a rocky ledge in the Himalayas. Its thick fur is covered with a light dusting of snow. It pauses, turning its head to look directly into the camera, its breath visible in the cold air. The background shows snow-covered peaks and a pale blue sky. National Geographic documentary style, photorealistic, extremely detailed.

A lone samurai in a small wooden boat navigating a stormy sea, in the ukiyo-e style of Hokusai's "The Great Wave". A giant, serpentine water dragon with glowing eyes rises from the stylized, swirling waves. The sky is a flat, pale yellow. Japanese woodblock print style, dramatic, mythical.

A chaotic food fight in a kitchen, rendered in a vibrant claymation style. A clay figure of a chef ducks as a pie flies over his head in slow motion, splattering against the wall. We can see fingerprints and tool marks on the clay characters. Playful, stop-motion animation, tactile textures.

A POV shot from a person riding a steam-powered monorail through a bustling steampunk city. Below, crowds in Victorian attire walk past intricate brass automatons. Giant clockwork gears turn slowly between skyscrapers adorned with copper pipes and billowing smoke. Sepia tone, highly detailed, industrial atmosphere.

A beautiful woman in elegant Tang Dynasty attire plays a pipa under a blooming cherry blossom tree in a traditional Chinese courtyard. Petals gently fall around her. A stone table nearby holds a set of delicate teaware. The scene is shot with a soft, diffused light, creating a poetic and serene mood. Chinese painting style (Guohua), historical realism, tranquil.

A surreal, dreamlike scene where a giant, antique clock face melts over a desert of black sand, in the style of Salvador Dali. A lone figure in a flowing red cloak walks towards a doorway that opens into a star-filled galaxy. The atmosphere is silent and mysterious. Oil painting style, symbolic, high contrast.

A cozy, cluttered kitchen in the Ghibli anime style. A young girl with short brown hair stands on a stool, carefully pouring milk into a bowl of flour. Sunlight streams through a window, illuminating dust motes dancing in the air. A fat, fluffy cat is sleeping on the warm windowsill. Hand-drawn animation style, warm and nostalgic, detailed background.

Related Models

README

Kling v2.1

Kling v2.1 is an AI video generation model developed by KlingAI (Kuaishou). It is purpose-built for creators, artists, and production teams seeking fast, realistic video generation from image and text prompts. Ideal for rapid prototyping, rough drafts, and creative iteration, it balances performance with affordability—while maintaining high-quality motion dynamics and visual coherence.

🔍 Overview

Kling 2.1 leverages 3D spatiotemporal attention, advanced motion synthesis, and cinematic camera simulation to transform static inputs into dynamic, photorealistic video clips. The i2v-standard variant provides a lightweight version for scalable generation tasks without sacrificing essential quality.

✨ Key Features

  • Smooth Motion

  • Advanced stabilization techniques ensure jitter-free movement across frames, even during complex sequences.

  • High-Fidelity Rendering

  • Realistic modeling of skin, fluids, materials, and reflections to preserve physical consistency.

  • Prompt Understanding

  • Enhanced context-aware interpretation of complex actions, camera directives, and stylistic cues.

  • Camera Control

  • Supports cinematic moves like dolly zooms, panning, and programmable motion paths for enhanced visual storytelling.

🎯 Use Cases

  • Short-Form Video Production

  • Generate fast and engaging clips for TikTok, YouTube Shorts, Instagram Reels, etc.

  • Storyboarding and Previsualization

  • Create visual drafts for films, ads, or animation projects with dynamic composition.

  • Promotional Content

  • High-resolution marketing videos for commercial brands or product showcases.

  • Artistic Video Creation

  • Stylized, experimental outputs suitable for NFTs, video art, and immersive storytelling.

  • Game and Simulation Previews

  • Generate scene previews for virtual environments and narrative cutscenes in game development.

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

Kling v2.1 T2v Master API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.1-t2v-master with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Kling v2.1 T2v Master below.

HTTP example
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.1-t2v-master" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "negative_prompt": "blurry, low quality, distorted",
    "aspect_ratio": "16:9",
    "duration": 5,
    "guidance_scale": 0.5
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].
Node.js example
// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("kwaivgi/kling-v2.1-t2v-master", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "negative_prompt": "blurry, low quality, distorted",
        "aspect_ratio": "16:9",
        "duration": 5,
        "guidance_scale": 0.5
});

console.log(result.outputs[0]); // → URL of the generated output
Python example
# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "kwaivgi/kling-v2.1-t2v-master",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "negative_prompt": "blurry, low quality, distorted",
    "aspect_ratio": "16:9",
    "duration": 5,
    "guidance_scale": 0.5
}
)

print(output["outputs"][0])  # → URL of the generated output

Kling v2.1 T2v Master API — Frequently asked questions

What is the Kling v2.1 T2v Master API?

Kling v2.1 T2v Master is a Kuaishou model for video generation, exposed as a REST API on WaveSpeedAI. Kling v2.1 creates cinematic 5-10s videos at 720p or 1080p from a single image or text prompt with improved motion fidelity and coherence. 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 v2.1 T2v Master 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 prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/kwaivgi/kwaivgi-kling-v2.1-t2v-master.

How much does Kling v2.1 T2v Master cost per run?

Kling v2.1 T2v Master starts at $1.30 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 v2.1 T2v Master accept?

Key inputs: `prompt`, `aspect_ratio`, `duration`, `guidance_scale`, `negative_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-v2.1-t2v-master.

How long does Kling v2.1 T2v Master take to generate?

Average end-to-end generation time on WaveSpeedAI is around 370 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Kling v2.1 T2v Master 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.