Run Kling's latest and most capable video model online or via API. Native 4K, multi-shot generation, 3-15s clips with synchronized audio, motion and element control.
Same interface you get inside the app. Drop in a prompt or image, hit run. Sign in to generate.
Free account, pay only per second of video. Your inputs carry over.
run this in browser →runs on inference.sh · no GPU setup · cancel anytime
Kling V3 is the third-generation video model from Kling AI, built by the Chinese company Kuaishou. You give it a text prompt, a starting image, or both, and it generates a short video clip — now at native 4K with synchronized audio, where earlier versions topped out at 1080p and silent output.
The headline upgrades over V2 are multi-shot generation (a single prompt can produce a sequence of camera angles instead of one continuous take), finer motion and element control, and flexible 3 to 15 second durations billed per second so you only pay for the length you need. It is a strong fit for cinematic b-roll, social and UGC ads, and product or character shots where camera movement matters.
Because it is a closed, API-only model, you cannot self-host it — you run it through a provider. On inference.sh you call it with the same API key and billing as every other model, with no per-vendor signup.
Real generations. Hover any clip in the app to see the exact prompt and settings.
The full schema, in plain English. Defaults are sensible — change these when you need to.
One key, one bill, every model. This is the standard inference.sh API reference for klingai/video-v3.
Kling V3.0 — latest and most capable video generation model. Native 4K output, multi-shot generation, flexible 3-15s duration billed per second, element control, motion control, and synchronized audio.
Install the client, set your API key, then submit a request and wait for the result — or stream live progress.
The API uses API keys for authentication. Set INFERENCE_API_KEY as an environment variable. See the authentication docs for detailed setup.
File inputs are handled automatically by the SDK. The Python SDK detects local file paths and uploads them; URLs are passed through as-is. You can pass local paths, URLs, or base64 data.
Get notified when a task completes by providing a webhook URL. When the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your URL with the task result.
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output
Sign in and generate your first 4K clip in a click. Pay per second, no setup.
run in browser →