A10 vs T4

Dense FP16 arithmetic on the A10 reaches 125 TFLOPS while the T4 reaches 65 TFLOPS so the A10 supplies nearly twice the dense FP16 rate. The same ratio appears when sparse FP16 figures are compared at 250 TFLOPS versus the T4 dense FP16 value of 65 TFLOPS. FP32 throughput follows a larger gap with the A10 at 31.2 TFLOPS against the T4 at 8.1 TFLOPS. Memory bandwidth of 600 GB/s on the A10 versus 320 GB/s on the T4 permits larger batch sizes before the workload becomes bandwidth bound. INT8 dense throughput of 250 TOPS on the A10 compared with 130 TOPS on the T4 indicates similar scaling for quantized inference workloads. All ratios remain within the supplied dense or sparse categories without mixing the two.

Its 600 GB/s bandwidth supports larger batches during training or fine tuning sessions that would otherwise spill to system memory on the T4. Scientific computing jobs that rely on the 31.2 TFLOPS FP32 rating also favor the A10 when throughput per card matters more than the lower 70 W TDP of the T4.

The T4 fits inference pipelines that remain inside 16 GB VRAM and that tolerate 65 TFLOPS dense FP16. Its 70 W TDP reduces power draw in dense server deployments where many cards operate simultaneously. Quantized INT8 inference at 130 TOPS meets latency targets for lighter models without requiring the higher 150 W TDP or the additional 8 GB of VRAM supplied by the A10.