RTX 2070 vs RTX 2080

Dense FP16 performance of 40.3 TFLOPS on the RTX 2080 exceeds the 29.9 TFLOPS dense FP16 figure on the RTX 2070 by a ratio of 1.35. This gap accelerates tensor operations during both training and inference workloads that rely on half precision arithmetic. The RTX 2080 also records 10 TFLOPS FP32 compared with 7.5 TFLOPS FP32 on the RTX 2070. Memory bandwidth stays fixed at 448 GB/s for both cards so maximum batch sizes remain comparable when memory capacity permits. Dense INT8 throughput reaches 161.1 TOPS on the RTX 2080 versus 119.4 TOPS on the RTX 2070. The higher TDP of 215 W on the RTX 2080 accompanies these elevated throughput numbers while the RTX 2070 operates at 175 W.

The RTX 2070 suits deployments that prioritize lower power draw at 175 W. Systems with constrained cooling or electricity budgets benefit from its 7.5 TFLOPS FP32 and 29.9 TFLOPS dense FP16 ratings. The fixed 8 GB VRAM and 448 GB/s bandwidth still support moderate inference loads that do not require the additional capacity offered by the RTX 2080.

The RTX 2080 fits workloads that demand higher dense FP16 throughput at 40.3 TFLOPS and FP32 throughput at 10 TFLOPS. Its option for up to 11 GB VRAM alongside the same 448 GB/s bandwidth enables larger batch processing than the RTX 2070.