KuaishouKuaishou·🎬 Video Generation

Kling V3 Turbo Standard

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Quick reference
Kling V3 Turbo Standard — TLDR
  • 🎬 Text-to-video generation from Kuaishou's Kling family
  • ⚡ Turbo-tier pipeline tuned for faster output
  • 🎨 Cinematic quality, strong human motion and editorial scenes
  • 🎯 Standard tier — lighter sibling to Turbo Pro
  • 🏢 Built by Kuaishou, makers of the Kwai app
💰 Pricing
$0.370 – $1.85
per generation
📅 On Venice since
Jun 17, 2026
46 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 V3 Turbo Standard is Kuaishou's speed-optimized text-to-video generator, turning written prompts into cinematic clips with the Kling line's signature strength in realistic human motion and editorial scene composition. Released in June 2026, it sits in the "Turbo" branch of the Kling V3 generation, where Kuaishou trades a measure of maximum fidelity for noticeably faster generation — making it well suited to iterative drafting and higher-volume creative work.

Within the lineup, this Standard tier is the lighter, more economical companion to Kling V3 Turbo Pro, which shares the same June 2026 release but targets higher production quality. It also has an image-driven counterpart, Kling V3 Turbo Standard (image-to-video), for animating still frames. Users wanting maximum resolution can look to siblings like Kling V3 4K.

Choose Kling V3 Turbo Standard when you want quick, prompt-driven video with believable character movement and a film-like look, and when turnaround speed and cost-efficiency matter more than squeezing out the last increment of detail.

This About section is AI-generated from public sources (Claude Opus 5), with no human editing. It may contain inaccuracies — verify critical details against the sources listed above.

Data sources: Venice API · HuggingFace · Wikipedia — enrichment updated 3d ago