B300 vs GTX 1080

The FP16 dense performance of 2250 TFLOPS on the B300 enables much larger scale operations than the GTX 1080 which has no published FP16 figure. This delta means the B300 supports training and inference at scales where the GTX 1080 cannot match due to its 8.9 TFLOPS FP32 limit. Memory bandwidth of 8000 GB/s on the B300 allows for substantially larger batch sizes compared to 320 GB/s on the GTX 1080. FP8 dense reaches 4500 TFLOPS on the B300 further extending its advantage in precision reduced workloads. The 1400W TDP of the B300 contrasts with the 180W TDP of the GTX 1080 indicating different power and cooling requirements for sustained performance. Real world implications include the B300 handling models that require high VRAM capacity of up to 288 GB whereas the GTX 1080 limits users to 11 GB maximum. Ratios between FP32 figures show the B300 at 75 TFLOPS exceeding the GTX 1080 by a factor derived from these numbers alone.

The B300 suits scenarios that require 2250 TFLOPS FP16 dense performance along with 8000 GB/s memory bandwidth and up to 288 GB VRAM capacity. Workloads involving large scale model training or inference benefit from the B300 FP8 dense at 4500 TFLOPS and its SXM6 form factor with NVLink interconnect. Users select the B300 when FP4 dense at 13500 TFLOPS supports reduced precision tasks that exceed GTX 1080 capabilities.

The GTX 1080 fits environments constrained to 180W TDP and PCIe form factor with PCIe 3.0 interconnect. Tasks limited to 8.9 TFLOPS FP32 and 11 GB maximum VRAM align with the GTX 1080 when power efficiency at lower scales takes priority over tensor performance. The GTX 1080 serves legacy systems that do not require published FP16 or higher bandwidth figures.