The network bandwidth requirements for large model video processing depend on several factors, including the resolution and frame rate of the video, the complexity of the model, the batch size, and whether the processing is done in real-time or batch mode.
Key Factors Affecting Bandwidth Requirements:
-
Video Resolution & Frame Rate
- High-resolution videos (4K/8K) require significantly more bandwidth than 1080p or 720p.
- Higher frame rates (60fps vs. 30fps) increase data transfer needs.
-
Model Complexity
- Large vision models (e.g., CLIP, ViT, or diffusion models) process high-dimensional data, requiring fast data ingestion.
- Multi-modal models (video + text/audio) need additional bandwidth for auxiliary inputs.
-
Batch Processing vs. Real-Time
- Batch processing (offline) can tolerate lower bandwidth if data is preloaded.
- Real-time processing (live streaming, video conferencing) demands high-throughput, low-latency networks (e.g., 100 Mbps to 10 Gbps+).
-
Data Transfer Between Nodes
- Distributed training/inference requires high-bandwidth interconnects (e.g., 10Gbps+ for GPU clusters).
Estimated Bandwidth Requirements:
| Use Case |
Resolution |
Frame Rate |
Estimated Bandwidth |
| Offline Video Analysis |
1080p |
30fps |
10-50 Mbps |
| Real-Time Video AI |
1080p |
30-60fps |
50-200 Mbps |
| 4K Video Processing |
4K (2160p) |
30fps |
200 Mbps - 1 Gbps |
| 8K Video + AI |
8K (4320p) |
30fps |
1-5 Gbps+ |
| Real-Time Multi-Stream |
Multiple 1080p |
30fps |
1 Gbps+ (per stream) |
Example Scenarios:
-
Video Surveillance AI (1080p, 30fps)
- A system analyzing 10 cameras in real-time may need ~1-2 Gbps aggregate bandwidth.
-
4K Video Editing with AI Effects
- Applying AI filters (e.g., background removal, super-resolution) to 4K footage requires ~500 Mbps - 1 Gbps for smooth processing.
-
Cloud-Based Video Training (8K Datasets)
- Uploading large video datasets (8K, 60fps) to the cloud for model training may need 1-10 Gbps for efficient data transfer.
Recommended Solutions (Tencent Cloud Services)
For high-performance video processing, Tencent Cloud offers:
- High-Throughput Cloud Storage (COS) – Optimized for large video file transfers.
- Elastic Network (VPC, ENI) – Ensures low-latency, high-bandwidth connectivity.
- GPU Accelerated Instances (GN-series) – Ideal for real-time AI video inference.
- Content Delivery Network (CDN) – Reduces latency for distributed video processing.
Choosing the right bandwidth depends on specific use cases, but 1 Gbps+ is often recommended for 4K+ real-time AI video tasks.