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Kling Std v2.1 is a robust image-to-video model that generates short, consistent videos from a single image. It focuses on temporal stability, smooth motion, and faithful visual detail, making it a dependable choice for product demos, concept visualizations, and social media content. Need higher fidelity and more expressive motion? Try Kling Pro v2.1.

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Key capabilities

  • Smooth, realistic motion generation from one input image
  • Strong temporal consistency with minimal flicker
  • Natural color and lighting preservation
  • Good detail retention on faces, products, and environments

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Use cases

  • Product showcases: animate angles or subtle movements from a hero image
  • Marketing and social: create short video loops for ads and posts
  • Concept visualization: bring static artwork or renders to life
  • UI/UX motion previews: generate simple motion studies from mockups
  • Educational content: illustrate processes with gentle camera moves

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Generate a video with Kling Std v2.1

Create an image-to-video task using the Kling v2.1 Standard model.

POST /v1/ai/image-to-video/kling-v2-1-std

Generate video from an image

GET /v1/ai/image-to-video/kling-v2-1-std

List image-to-video tasks

GET /v1/ai/image-to-video/kling-v2-1/{task-id}

Check task status

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Frequently Asked Questions

Use high-resolution images with clear subjects, clean backgrounds, and balanced lighting. JPEG/PNG are recommended. Avoid heavy compression and noisy inputs.
Video duration depends on model defaults and parameters from the API. Kling Std v2.1 is geared toward short clips ideal for previews and social formats.
Yes. The model can synthesize gentle camera moves and subject motion while maintaining temporal stability. Complex motion may require careful prompting and tuning.
Std focuses on reliable, general‑purpose quality with good consistency. Pro and Master variants target higher fidelity or more advanced motion control. Choose Std for dependable everyday use cases.

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Best practices for image‑to‑video

  • Start with clean, well‑lit images at sufficient resolution.
  • Keep subjects centered and avoid busy backgrounds for clearer motion focus.
  • Use moderate motion expectations; evaluate results before increasing complexity.
  • Ensure branding, faces, and key details are unobstructed for better consistency.
  • Validate outputs at target aspect ratios and durations for your platform.