Table of Contents
Most CV deployments aren't single-stream — they're N cameras feeding one GPU. The 5060 Ti handles meaningful camera fleets.
TL;DR
RTX 5060 Ti 16 GB hosts ~16 concurrent 30-FPS YOLOv8m streams at 640×640, or ~8 streams of YOLOv8x. Triton Inference Server with dynamic batching is the right runtime.
Multi-stream architecture
- Triton Inference Server: dynamic batching across streams
- NVIDIA DeepStream: full pipeline (decode + inference + analytics)
- FastAPI + custom batcher: lightweight, more control
Concurrent stream limits
| Workload | Concurrent streams (30 FPS each) |
|---|---|
| YOLOv8n 640×640 | ~80 |
| YOLOv8s 640×640 | ~40 |
| YOLOv8m 640×640 | ~16 |
| YOLOv8l 640×640 | ~12 |
| YOLOv8x 640×640 | ~8 |
| YOLOv8x 1280×1280 | ~3 |
Verdict
For small camera fleets (8-16 cameras), the 5060 Ti is the cost-leading host. Above that, scale to a 5080 or 5090.
Bottom line
For multi-camera CV at small scale, RTX 5060 Ti at £119/mo is the right starting hardware. See YOLOv8 benchmark.
