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Kling v2.1 Master Text to Video

Fast Inference
REST API
Model Information
Response Time:~0 sec
Status:Active
Version:
0.0.1
Updated:11 days ago

kling-v2-1-master-text-to-video

Live Demo
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Input

Configure model parameters

Output

View generated results

Result

Preview, share or download your results with a single click.

Overview

Kling v2.1 Master Text to Video is a generative video model that transforms text prompts into short video clips. By combining coherent motion dynamics with accurate visual storytelling, Kling v2.1 can synthesize temporally consistent video content from a single textual description. It supports a wide range of subjects, including characters, actions, and environments.

Technical Specifications

Kling v2.1 Master is a text-to-video generation model with a temporal attention mechanism to maintain consistency across frames.

Outputs are synthesized at a consistent frame rate and resolution, with adaptive motion modeling based on subject and context. 

Internal optimizations reduce flickering and improve object persistence across motion sequences.

Key Considerations

Kling v2.1 currently does not support audio generation.

Kling v2.1 Master Text to Video performs best when no complex scene transitions or multi-prompt edits are included.

Kling v2.1 does not handle long-range narratives. Keep descriptions focused on a single moment or action.

Some subjects, especially involving abstract or surreal input, may generate inconsistent results.


Legal Information for Kling v1 Pro Image to Video

By using this Kling v1 Pro Image to Video, you agree to:

Tips & Tricks

prompt
Use detailed descriptions with visual anchors. Good: "A man surfing on a big blue wave during sunset"
Bad: "Adventure mood with excitement"

duration (5–10)
Select the duration based on action length.

  • Use 5 for static or single-action shots
  • Use 8–10 for dynamic motion like running, dancing, or panning

aspect_ratio
Match the layout with your subject:

  • 16:9 for wide landscapes or cinematic views
  • 9:16 for single-person vertical framing
  • 1:1 for symmetrical or centered subjects

negative_prompt
Actively remove unwanted traits:

  • Example: "text, watermark, distortion, low quality"

cfg_scale (0.0–1.0)

  • 0.6–0.7 for stylized or abstract visuals
  • 0.8–0.9 for more literal, prompt-accurate scenes
  • Avoid using 1.0 unless prompt is extremely clean and unambiguous

Capabilities

Generates short video clips from textual descriptions

Handles basic character actions (e.g., walking, turning, waving)

Interprets environmental context such as weather, time of day, and terrain

Supports motion effects like zoom, pan, and wave movement

What can I use for?

Creating short visual scenes for storytelling

Visualizing motion for creative writing or scripts

Generating animated video snippets for character design

Experimenting with visual ideation before animation or filming

Things to be aware of

Use 9:16 ratio and portrait-focused prompts to simulate smartphone-style videos 

Combine motion words like "dancing", "spinning", "gliding" to guide the animation

Use setting words like "in the forest", "on a rooftop" for consistent backgrounds

Limitations

Cannot produce audio or subtitles

Complex choreography or multi-character interactions may lack accuracy

Some outputs may include visual artifacts such as flickering or blurred details

Not suitable for long-form content or continuity across multiple scenes

Output Format: MP4

Kling v2.1 Master Text to Video | AI Model | Eachlabs