Table of Contents
Computer vision workloads have different characteristics than LLM serving — small models, high batch parallelism, throughput-bound. The 5060 Ti is a strong CV host at the entry tier.
RTX 5060 Ti 16 GB hosts YOLOv10x at ~120 FPS, SAM 2 at ~30 segmentation/sec, ResNet-50 at ~3,500 inferences/sec. Plenty for a single-camera or low-volume CV pipeline.
Workloads that fit
- Object detection: YOLOv8 / YOLOv10 / RT-DETR
- Segmentation: SAM 2, Mask2Former
- Image classification: ResNet, ConvNeXt, ViT
- OCR: PaddleOCR, EasyOCR
- Image generation: SDXL, FLUX.1 schnell
- Vision-language: Qwen 2.5 VL 7B
Performance
| Model | Workload | FPS / throughput |
|---|---|---|
| YOLOv10x | 640×640 detection | ~120 FPS |
| YOLOv8n | 640×640 detection | ~520 FPS |
| SAM 2 large | Segmentation | ~30 / sec |
| ResNet-50 FP16 | 224×224 classification | ~3,500 / sec |
| ViT-L/16 | 224×224 classification | ~1,200 / sec |
| PaddleOCR | A4 page OCR | ~12 pages/sec |
Verdict
For most CV workloads at the entry tier, the 5060 Ti is over-spec’d — even cheaper cards (RTX 3050, RTX 4060) work for single-stream CV. The 5060 Ti is the right pick when CV is alongside an LLM (e.g., document AI = OCR + LLM summary).
Bottom line
For pure CV-only deployments, an RTX 3050 6 GB at £79/mo is sufficient for most workloads. The 5060 Ti shines when CV is one of multiple models on the same card.
