KuaishouKuaishou·🎬 Video Generation·New

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, speed-optimized standard quality variant
  • 🎨 Cinematic output, strong human motion and editorial scenes
  • 🏢 Built by Kuaishou, maker of the Kwai app
  • ⚡ Newest Turbo Standard line, released mid-2026
💰 Pricing
$0.370 – $1.85
per generation
📅 On Venice since
Jun 17, 2026
1 day 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 a focus on natural human motion and editorial-style scenes. Released in June 2026, it sits in the "Turbo" branch of the Kling V3 generation, where standard quality is paired with faster turnaround — a practical middle ground between raw render time and visual polish.

Within Kuaishou's lineup it pairs directly with Kling V3 Turbo Pro, the higher-fidelity Turbo sibling, and with Kling V3 Turbo Standard image-to-video, which animates a supplied still instead of a text prompt. It also stands alongside the broader V3 family, including the quality-first Kling V3 Pro and the high-resolution Kling V3 4K, plus the newer Kling O3 series.

This Turbo Standard tier is best suited to creators who want quick, repeatable text-to-video iterations — storyboards, social clips, and editorial shots — where fast generation and dependable human movement matter more than maximum resolution. For final-grade output, the Pro and 4K variants offer more headroom.

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 12h ago