RTX 4070 vs RTX A4000

The RTX 4070 FP32 figure of 29.1 TFLOPS exceeds the RTX A4000 figure of 19.2 TFLOPS which translates to faster execution of single precision workloads such as certain scientific simulations. Sparse FP16 throughput on the RTX A4000 reaches 153.4 TFLOPS compared with 116.6 TFLOPS on the RTX 4070 which indicates the RTX A4000 can accelerate sparsity enabled inference or training steps when the workload exploits that feature. The RTX 4070 dense FP16 figure of 58.3 TFLOPS has no direct counterpart published for the RTX A4000 so direct dense comparison remains unavailable. Memory bandwidth of 504 GB/s on the RTX 4070 versus 448 GB/s on the RTX A4000 affects achievable batch sizes during model training or inference with the higher bandwidth supporting larger batches before memory becomes the limiter. The 200W TDP of the RTX 4070 versus the 140W TDP of the RTX A4000 further influences sustained performance in power constrained cloud environments where thermal and power limits apply.

The RTX 4070 suits workloads that require the published dense FP16 throughput of 58.3 TFLOPS or the FP32 throughput of 29.1 TFLOPS. Its 504 GB/s memory bandwidth also favors scenarios that move large intermediate tensors where the extra bandwidth reduces stalls compared with the 448 GB/s available on the RTX A4000.

The RTX A4000 suits workloads that can exploit its sparse FP16 throughput of 153.4 TFLOPS and that benefit from its 16 to 20 GB memory capacity. Its 140W TDP further suits deployments where lower power draw per GPU is prioritized over the higher TDP of 200W on the RTX 4070.