RTX 3080 vs RTX 5060 Ti

The RTX 3080 outperforms the RTX 5060 Ti in raw compute with 29.8 TFLOPS FP16 and FP32 compared to 23.1 TFLOPS, translating to faster training and inference speeds by approximately 29 percent in FP16/FP32 bound workloads. This delta means the RTX 3080 handles larger models or higher throughputs more effectively during training phases requiring sustained tensor operations.

Memory bandwidth reveals a key disparity: 760 GB/s on the RTX 3080 versus 448 GB/s on the RTX 5060 Ti. Higher bandwidth supports larger batch sizes in inference and training, reducing data transfer bottlenecks and enabling 69 percent more throughput for memory-intensive tasks like large language model processing. The RTX 5060 Ti's GDDR7 VRAM and Blackwell architecture may offer better efficiency per watt, but its lower specs limit scalability in high-demand scenarios.

Power consumption differs significantly at 320 W for RTX 3080 against 180 W for RTX 5060 Ti, favoring the latter for dense deployments where cooling and energy costs matter.

Select the RTX 3080 for workloads demanding maximum compute throughput, such as LLM training or Stable Diffusion generation requiring 29.8 TFLOPS FP16/FP32 performance. Its 760 GB/s bandwidth excels in handling large batch sizes, making it ideal for data-heavy scientific computing or fine-tuning where speed trumps efficiency. At $0.06 per hour starting price, it delivers superior value for performance-critical cloud rentals.

Choose the RTX 5060 Ti when power efficiency drives decisions, with its 180 W TDP versus 320 W on the RTX 3080 suiting multi-GPU setups or cost-sensitive environments. The Blackwell architecture and 12 GB GDDR7 VRAM provide modern features for inference tasks at $0.07 per hour, benefiting deployments prioritizing lower operational costs over peak TFLOPS.