Kling v2.5 Turbo Pro Text-to-Video API by Kuaishou

Kling 2.5 Turbo Pro (Text-to-Video)

Kling 2.5 Turbo Pro is an advanced text-to-video model that produces ultra-smooth motion, cinematic visuals, and accurate prompt adherence.

Its improved dynamic processing and text-to-motion control allow for seamless transitions while maintaining style fidelity across various looks.

What makes it different?

• Enhanced multi-step instruction understanding A new text-and-timing controller processes multi-step prompts to transform static inputs into coherent, controllable narrative scenes.

• High-motion quality and stability Better training and data balance create realistic dynamics, enabling quick and complex movements with fewer artifacts like jitter, tearing, or frame drops.

• Faster inference Optimized pipelines reduce end-to-end delay, providing faster delivery of high-quality results without compromising visual fidelity.

• Consistent style Enhanced style conditioning preserves the reference look (palette, lighting, brushwork, mood), ensuring frames stay consistent - even during dynamic scenes.

Designed for

• Marketing & Brand Teams – Produce style-consistent ads, feature demos, and campaign assets fast.
• Content Creators / YouTubers / Short-form Teams – Improve watch-through with stronger narrative flow and motion.
• Film/Animation Studios – Use for previz, technique exploration, and style studies with reliable dynamic consistency.
• Training & Education – Turn documents into clear, high-resolution explainer videos for scalable distribution.

Pricing

Billing Rules

• Minimum charge: 5 seconds
• Per-second rate = (price per 5 seconds) ÷ 5
• Billed duration = video length in seconds (rounded up), with a 5-second minimum
• Total cost = billed duration × per-second rate (by output resolution)

How to use

1. Write the prompt – Specify subject, scene, actions, camera movement, and style keywords; include multi-step/causal logic if needed.

2. Choose aspect – Match output to your channel and quality targets.

3. Set duration – Help models understand how long of the result.

4. Set guidance_scale – Controls how strongly the model follows your prompt. The higher the value, the less creative freedom the model has.

5. Generate – Leverage accelerated inference to get a first pass quickly.

6. Review & iterate – Refine timing, angles, or style strength and re-render for final delivery (Set the seed).