Kwai

Kling 3.0 Pro

Advanced generative video architecture with physical simulation consistency, multi-angle camera trajectory, and 4K temporal coherence.

#24发布于 2026年10月1日·Proprietary·Not disclosed
textvideo64K ctx
智商指数
88.6 #24
AAQI 88.0
输出速度
25 t/s
ITL 40.0 ms/tok
混合价格 (3:1)
$0.1 /1M
输入 $0.1/M · 输出 $0.1/M
上下文
64K
≈ 160 页 A4 · 最大输出 2,048

Quality Domain Radar

6-Axis Frontier Evaluation vs Category Average & Flagship

Kling 3.0 Pro
Claude Mythos Preview (#1)
Average (68)
Coding (15)Mathematics (15)Hard Science (GPQA) (40)Agentic & Tool Use (25)Knowledge (MMLU) (60)Vision / Multimodal (98.8)

缺少直接基准测量时,雷达图各轴由类别得分近似得出 — 详见 评分方法。

优势与取舍

优势所在

  • Beats Veo/Seedance-class rivals in blind professional evals
  • Strong physics — cloth, fluids, collisions stay coherent
  • Excellent image-to-video identity retention

需要注意的权衡

  • No native audio track — pair with a TTS/score pipeline
  • Queue latency on long 1080p generations
  • English prompt adherence weaker than Chinese

杀手级用例

UGC ad clips
Short-form product and lifestyle ads at scale.
Previz & storyboards
Animated storyboards with consistent characters.
Product demos
Motion shots from a single reference image.

开发者快速上手与 API

请先设置 KLING_API_KEY — 获取 API 密钥
curl -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"
  }'

Async video API — submit a task, then poll the task_id until the clip is ready.

官方资源与链接

API 部署

对比托管商与延迟

Groq、Cerebras、Together、DeepInfra、Fireworks、Bedrock 与 Azure 的吞吐量、TTFT 和缓存定价。

GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
查看提供商矩阵 →

各榜单得分

实时规格与架构

底层解析
Kling 3.0 — diffusion-transformer video model
  • 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
发布日期
2026年10月1日
架构
Kling 3.0 — diffusion-transformer video model
参数量
Not disclosed
开源协议
Proprietary
上下文窗口
64,000 tokens
最大输出
2,048 tokens
模态
text + video
缓存价格
读 $0.02 · 写 $0.1 /1M
推理
—
输入价格
$0.1/M
输出价格
$0.1/M
输出速度
25 t/s
首Token延迟
—
数据更新
2026年10月5日

每月账单预估

每月预估支出
$0.00
正在计算相对 GPT-4o 的节省额…

引用与嵌入

GitHub Markdown 徽章
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BibTeX
@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}
}

嵌入评分徽章

将实时 Podium 评分徽章添加到 GitHub 或 Hugging Face README —— 链接回实时排名。

预览
Kling 3.0 Pro LLMPodium Score
Markdown
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