Kling 3.0 Pro
Advanced generative video architecture with physical simulation consistency, multi-angle camera trajectory, and 4K temporal coherence.
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Radar-Achsen sind aus Kategorie-Scores approximiert, wo direkte Benchmark-Messungen fehlen — siehe Methodik.
Stärken & Trade-offs
Wo das Modell gewinnt
- Beats Veo/Seedance-class rivals in blind professional evals
- Strong physics — cloth, fluids, collisions stay coherent
- Excellent image-to-video identity retention
Worauf achten
- No native audio track — pair with a TTS/score pipeline
- Queue latency on long 1080p generations
- English prompt adherence weaker than Chinese
Killer-Anwendungsfälle
Developer-Quickstart & API
KLING_API_KEY — API-Schlüssel holencurl -X POST "https://api.klingai.com/v1/videos/text2video" \
-H "Authorization: Bearer $KLING_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model_name": "kling-v3-0-pro",
"prompt": "A drone shot gliding over a rainy neon city at night",
"duration": "5",
"aspect_ratio": "16:9"
}'import os, requests
resp = requests.post(
"https://api.klingai.com/v1/videos/text2video",
headers={"Authorization": f"Bearer {os.environ['KLING_API_KEY']}"},
json={
"model_name": "kling-v3-0-pro",
"prompt": "A drone shot gliding over a rainy neon city at night",
"duration": "5",
"aspect_ratio": "16:9",
},
)
print(resp.json()["data"]["task_id"]) # poll until doneconst res = await fetch("https://api.klingai.com/v1/videos/text2video", {
method: "POST",
headers: { Authorization: `Bearer ${process.env.KLING_API_KEY}`, "Content-Type": "application/json" },
body: JSON.stringify({
model_name: "kling-v3-0-pro",
prompt: "A drone shot gliding over a rainy neon city at night",
duration: "5",
aspect_ratio: "16:9",
}),
});
console.log((await res.json()).data.task_id); // poll until doneAsync video API — submit a task, then poll the task_id until the clip is ready.
Offizielle Ressourcen & Links
Hosts & Latenz vergleichen
Durchsatz, TTFT und Cache-Preise bei Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock und Azure.
Ergebnisse nach Quelle
Kategorie-Punkte
Benchmark-Ergebnisse
Live-Spezifikationen & Architektur
- Physical-simulation consistency across frames
- Multi-angle camera coherence and motion control
- Pro tier: 1080p output with multi-shot control
- Text-to-video and image-to-video pipelines
Geschätzte Monatsrechnung
Zitieren & Einbetten
Loading badge markdown...@misc{llmpodium2026kling30pro,
title = {Benchmark Analysis and Intelligence Evaluation of Kling 3.0 Pro},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/kling-3-0-pro}
}Score-Badge einbetten
Fügen Sie Ihrem GitHub- oder Hugging-Face-README ein Live-Podium-Score-Badge hinzu — es verlinkt auf das Live-Ranking.
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