A100 SXM4 40GB vs RTX 3090 Ti

The FP16 dense performance of 312 TFLOPS on the A100 family contrasts with the 35.6 TFLOPS FP16 figure on the RTX 3090 family where sparsity is not specified. This gap implies that training and inference tasks using dense FP16 operations complete faster on the A100 SXM4 40GB variant. FP32 throughput measures 19.5 TFLOPS for the A100 family against 35.6 TFLOPS for the RTX 3090 family so certain single precision workloads favor the RTX 3090 Ti. Memory bandwidth of 2039 GB/s shared across A100 variants enables larger batch sizes compared to the 936 GB/s of the RTX 3090 family. The A100 SXM4 40GB variant with its 40 GB HBM2e memory accommodates bigger models than the 24 GB GDDR6X on the RTX 3090 Ti. Sparse FP16 performance reaches 624 TFLOPS on the A100 family while dense INT8 reaches 624 TOPS.

The A100 SXM4 40GB variant suits scenarios that demand 40 GB of memory and high dense FP16 throughput of 312 TFLOPS. Workloads involving large scale model training benefit from the SXM4 form factor and 2039 GB/s bandwidth shared by the A100 family.

The RTX 3090 Ti serves applications where FP32 performance at 35.6 TFLOPS and a 350W TDP provide adequate capacity with 24 GB memory. Inference tasks that align with its PCIe form factor and NVLink interconnect may select this variant.