A10 vs RTX 4080

The A10 supplies 125 TFLOPS of dense FP16 performance against the RTX 4080 supply of 97.5 TFLOPS of dense FP16 performance. This gap means the A10 processes dense FP16 workloads at a higher rate than the RTX 4080. When sparsity is enabled the A10 reaches 250 TFLOPS of FP16 performance while the RTX 4080 reaches 195 TFLOPS of FP16 performance. Memory bandwidth stands at 600 GB/s on the A10 and 717 GB/s on the RTX 4080 so the RTX 4080 can move data faster per second despite its smaller memory pool. The A10 INT8 dense performance equals 250 TOPS while the RTX 4080 INT8 dense performance equals 389.9 TOPS indicating the RTX 4080 holds an advantage in that metric.

The A10 suits workloads that require 24 GB of memory and lower power consumption at 150 W. Its 125 TFLOPS of dense FP16 performance supports inference tasks where memory capacity limits batch sizes more than raw throughput. The card also provides 31.2 TFLOPS of FP32 performance for scientific computing that fits within its TDP envelope.

Its 389.9 TOPS of dense INT8 performance accelerates certain inference pipelines that scale with higher tensor throughput. The card fits environments where the 320 W TDP is acceptable in exchange for these metrics.