KuaishouKuaishou·🎬 Video Generation

Kling 2.6 Pro

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Quick reference
Kling 2.6 Pro — TLDR
  • 🎬 Text-to-video generation from Kuaishou's Kling family
  • 🎯 Pro-tier model tuned for cinematic quality
  • 🎨 Strong on human motion and editorial scenes
  • 🏢 Built by Kuaishou, maker of Kwai
  • 🌍 Prompt-driven clip generation, no input image needed
💰 Pricing
$0.390 – $1.54
per generation
📅 On Venice since
Dec 3, 2024
592 days ago
Provider

Kuaishou Technology is a Chinese publicly traded company founded in 2011 by Hua Su and Cheng Yixiao, headquartered in Beijing's Haidian District and listed on the Hong Kong Stock Exchange. Originally known for its massively popular short-video platform —…

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25 models on Venice
25 video
Since Dec 3, 2024

About this model

Kling 2.6 Pro is the text-to-video member of Kuaishou's Kling family, generating short cinematic clips directly from written prompts. Built by the Chinese short-video giant behind the Kwai app, the Kling line is engineered for photorealistic motion, with a particular reputation for natural human movement and polished, editorial-style scenes — the kind of footage that needs convincing bodies, faces, and camera work rather than abstract effects.

Within Kuaishou's lineup, the 2.6 Pro tier sits as a prior generation of the Pro text-to-video line, now succeeded by Kling V3 Pro (released February 2026) and the broader V3 and O3 generations that followed. It also has an image-to-video counterpart under the same Kling 2.6 Pro name for animating existing stills. Users may still choose this version deliberately for its specific look, cost, or output characteristics.

It is best suited for creators who want to produce cinematic, motion-rich video clips from a text description alone — promotional spots, narrative shots, and character-driven scenes where believable human movement and an editorial aesthetic matter most.

This About section is AI-generated from public sources (Claude Opus 4.8), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.

Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 4d ago