Kling Tutorial: Get Started in 5 Minutes [2026]

What it does:

Converts natural language scene descriptions into rendered video clips at up to 1080p resolution and 5 or 10 seconds in length using the Kling 3.0 large model. Users provide a text prompt describing the desired scene, camera movement, subject actions, and visual style, and the system generates a corresponding video. Supports various cinematic techniques including first-person perspective, tracking shots, and specific environmental settings.

Use case:

What it does:

Allows users to supply multiple reference images—such as specific accessories, clothing items, or character appearances—alongside a text prompt to guide generation. This gives significantly more compositional control than pure text prompting, enabling users to specify exact visual elements they want incorporated into the output video or image.

Use case:

What it does:

Generates product display videos automatically from product images and brief text descriptions. Supports interactive display with characters and product elements, covering categories including clothing, beauty, and consumer electronics. Designed for merchants to produce marketing materials in batch at reduced cost compared to traditional video production.

Use case:

What it does:

Provides RESTful API access to all of Kling's generation capabilities, enabling third-party developers to integrate AI video and image generation into their own platforms. Supports text-to-video, image-to-video, lip sync, video effects, elements reference, text-to-image, image-to-image, virtual try-on, and audio generation endpoints.

Use case: