Quadro P4000 vs RTX 3060 Ti

The RTX 3060 Ti delivers 12.7 TFLOPS in FP16 and FP32 performance, more than doubling the Quadro P4000's 5.3 TFLOPS in both metrics. This advantage accelerates deep learning training and inference: training epochs complete roughly 2.4 times faster on the RTX 3060 Ti assuming compute-bound workloads. FP16 parity with FP32 on both GPUs indicates reliance on standard shader performance without specialized tensor core boosts listed here.

Memory bandwidth stands out as a key differentiator: 360 GB/s on the RTX 3060 Ti versus 243 GB/s on the Quadro P4000. Higher bandwidth supports larger batch sizes in model training, reducing overhead and enabling efficient processing of datasets up to 48 percent larger before saturation. The RTX 3060 Ti's 12 GB VRAM further accommodates bigger models compared to 8 GB, minimizing out-of-memory errors in inference scenarios.

The Quadro P4000 suits legacy professional applications certified for Pascal-era Quadro cards, such as specific CAD or simulation software requiring ISV certifications. Its lower TDP of 105W fits power-constrained cloud instances where 170W exceeds limits. At $0.51 per hour, it remains viable if RTX 3060 Ti availability is low across 2 offers versus 6 for P4000.

The RTX 3060 Ti excels in modern AI and machine learning tasks due to 12.7 TFLOPS compute and 360 GB/s bandwidth. Its $0.03 per hour starting price delivers over 20 times better value than the P4000's $0.51 per hour. Larger 12 GB VRAM handles contemporary models effectively.