RTX 4080 vs RTX A6000

Dense FP16 performance stands at 97.5 TFLOPS on the RTX 4080 compared to 154.8 TFLOPS on the RTX A6000 while sparse FP16 reaches 195 TFLOPS versus 309.6 TFLOPS respectively. This gap indicates the RTX A6000 processes larger matrix operations in training workloads at higher throughput when sparsity is enabled. Memory bandwidth of 717 GB/s on the RTX 4080 versus 768 GB/s on the RTX A6000 limits batch size scaling on the RTX 4080 during inference of models that exceed 16 GB capacity. Dense INT8 ratings of 389.9 TOPS on the RTX 4080 exceed the 309.7 TOPS on the RTX A6000 and this favors the RTX 4080 in quantized inference paths that stay within its VRAM limit.

The RTX 4080 suits inference workloads that fit within 16 GB VRAM and require dense INT8 throughput of 389.9 TOPS. Its FP8 dense rating of 194.9 TFLOPS also supports precision sensitive tasks where the 48.7 TFLOPS FP32 figure provides an advantage over the RTX A6000. Users select the RTX 4080 when PCIe only connectivity meets system requirements and power draw of 320W remains acceptable.

The RTX A6000 fits training or fine tuning of models that demand 48 GB VRAM capacity. Its 154.8 TFLOPS dense FP16 rating and NVLink interconnect enable multi GPU scaling for scientific computing workloads that exceed single card memory. The 768 GB/s bandwidth further supports larger batch sizes than the 717 GB/s available on the RTX 4080.