RTX 2080 Ti vs RTX A6000

The FP16 dense performance of 40.3 TFLOPS on the RTX 2080 Ti variant contrasts with the FP16 dense performance of 154.8 TFLOPS on the RTX A6000 variant. This gap means the RTX A6000 variant processes matrix operations in training and inference at a higher rate when both figures are measured in dense mode. The FP32 performance of 10 TFLOPS on the RTX 2080 Ti variant stands against 38.7 TFLOPS on the RTX A6000 variant indicating faster single precision calculations on the latter. Memory bandwidth of 448 GB/s versus 768 GB/s affects the maximum batch sizes that fit within sustained data movement rates during large model operations. When sparsity is considered the RTX A6000 variant reaches FP16 performance of 309.6 TFLOPS with sparsity and INT8 performance of 619.4 TOPS with sparsity while the RTX 2080 Ti variant provides only dense figures of 40.3 TFLOPS for FP16 and 161.1 TOPS for INT8.

The RTX 2080 Ti variant with 11 GB GDDR6 memory suits scenarios where power draw must remain at 215W and workloads fit within that memory capacity. Its FP32 performance of 10 TFLOPS supports legacy applications that do not require the higher dense FP16 throughput of 154.8 TFLOPS found on newer variants. The lower TDP of 215W compared to 300W makes this variant preferable in systems with limited cooling or power delivery.

The RTX A6000 variant with 48 GB GDDR6 memory handles models that exceed the 11 GB capacity of the alternative variant. Its memory bandwidth of 768 GB/s paired with FP16 dense performance of 154.8 TFLOPS enables larger batch sizes during inference and training compared to the 448 GB/s and 40.3 TFLOPS on the RTX 2080 Ti variant. The PCIe 4.0 interconnect further supports higher data transfer rates in compatible systems.