T4 vs A100

Dense FP16 performance stands at 65 TFLOPS on the T4 compared to 312 TFLOPS on the A100 which indicates the A100 processes matrix operations at a ratio of 4.8 times the T4 rate during training workloads. The same dense FP16 comparison applies to inference where the A100 sustains higher throughput on identical precision tasks. Memory bandwidth at 320 GB/s for the T4 versus 2039 GB/s for the A100 allows the A100 to support larger batch sizes by a factor of 6.37 without data transfer constraints. FP32 ratios follow a similar pattern at 8.1 TFLOPS dense for the T4 against 19.5 TFLOPS dense for the A100 which favors the A100 for precision sensitive scientific calculations.

The T4 fits scenarios that prioritize low power draw at 70W TDP and PCIe form factor compatibility. Workloads limited to 16 GB VRAM and dense INT8 at 130 TOPS benefit from the T4 efficiency in constrained server environments. Inference tasks that do not require the 2039 GB/s bandwidth of the A100 align with T4 deployment where energy costs dominate operational considerations.

The A100 suits applications that demand 40 to 80 GB VRAM and dense FP16 at 312 TFLOPS for accelerated model processing. Training and inference pipelines that scale with 2039 GB/s bandwidth and 19.5 TFLOPS dense FP32 gain from the A100 specifications in multi GPU NVLink setups. High intensity tasks exceeding the T4 limits of 65 TFLOPS dense FP16 and 320 GB/s bandwidth select the A100 for sustained performance.