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Veo 3

每次請求:$0.4
Google DeepMind’s Veo 3 represents the cutting edge of text-to-video generation, marking the first time a large-scale generative AI model seamlessly synchronizes high-fidelity video with accompanying audio—including dialogue, sound effects, and ambient soundscapes.
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Core Features and Capabilities

  • 8‑Second Video Clips: Generates up to eight‑second sequences with seamless shot transitions and stitching.
  • Integrated Audio Generation: Produces dialogue, ambient noise, sound effects, and background music in a single pass.
  • High‑Definition Output: Supports resolutions up to 4K (3840 × 2160) with consistent lighting, realistic physics, and detailed scene textures.
  • Multi‑Modal Inputs: Accepts both text‑to‑video and image‑to‑video prompts, enabling versatile creative workflows.

These capabilities empower creators to craft near‑cinematic narratives without separate audio post‑production or complex editing pipelines .

Technical Details

Veo 3’s architecture leverages a multimodal transformer trained on millions of YouTube videos. Its encoder–decoder framework processes text prompts through a video tokenization layer, generating spatiotemporal features that drive the visual synthesis module. Simultaneously, an audio synthesis branch produces aligned sound outputs. A cross-modal attention mechanism ensures that visual and audio modalities remain tightly coupled, reducing desynchronization artifacts. Training involved billions of parameter updates, optimized via mixed-precision GPU clusters on Google Cloud’s Vertex AI platform .

Benchmark Performance

In internal benchmarks, Veo 3 demonstrates:

  • PSNR (Peak Signal‑to‑Noise Ratio) of 38 dB on standard video datasets, outperforming Veo 2 by 4 dB.
  • SSIM (Structural Similarity Index) scores of 0.92, indicating high visual fidelity.
  • Audio–Video Sync Error below 15 ms, ensuring imperceptible lag between sound and motion.
  • Inference Speed: ~12 frames per second on an NVIDIA A100 GPU, enabling near real-time generation for short clips.
    These metrics position Veo 3 at the forefront of generative video AI, eclipsing contemporaries like Sora and Meta’s recent video models in both quality and synchronization.
  • How to access Veo 3 API

Step 1: Sign Up for API Key

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.

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Step 2: Send Requests to Veo 3 API

Select the “\Veo 3 \” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account. base url is Veo3 Async Generation(https://api.cometapi.com/v1/videos).

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

Veo 3 的功能

了解 Veo 3 的核心能力,帮助提升性能与可用性,并改善整体体验。

Veo 3 的定价

查看 Veo 3 的竞争性定价,满足不同预算与使用需求,灵活方案确保随需求扩展。
Comet 价格 (USD / M Tokens)官方定价 (USD / M Tokens)折扣
每次請求:$0.4
每次請求:$0.5
-20%

Veo 3 的示例代码与 API

获取完整示例代码与 API 资源,简化 Veo 3 的集成流程,我们提供逐步指导,助你发挥模型潜能。

Veo 3 的版本

Veo 3 可能存在多个快照,原因包括:更新后保持一致性需要保留旧版、给开发者留出迁移窗口,以及全球/区域端点提供的优化差异。具体差异请参考官方文档。
veo3
veo3-framesThe veo3-frames model is specifically optimized for frame sequence generation.The veo3-frames model is specifically optimized for frame sequence generation, and includes a diagram supporting the first and last frames.

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