A100 SXM4 40GB vs RTX 5090

The A100 SXM4 40GB delivers 312 TFLOPS FP16 dense compared to the RTX 5090 at 209.5 TFLOPS FP16 dense which translates to superior throughput in dense matrix operations for training workloads. In sparse scenarios the A100 reaches 624 TFLOPS FP16 with sparsity against 419 TFLOPS FP16 with sparsity on the RTX 5090 allowing faster processing when sparsity optimizations apply. FP32 performance differs substantially with 19.5 TFLOPS on the A100 family versus 104.8 TFLOPS on the RTX 5090 family impacting general purpose computations. Memory bandwidth shared at 2039 GB/s for A100 variants and 1792 GB/s for RTX 5090 variants determines maximum data throughput rates during model execution. Higher bandwidth on the A100 supports larger batch sizes in memory constrained environments despite the lower FP32 rating. These metrics guide selection based on whether dense tensor performance or raw floating point throughput takes priority.

The A100 SXM4 40GB suits environments that require NVLink interconnect for multi GPU scaling and 40 GB memory capacity. Its 400W TDP provides lower power draw than the 575W rating of the RTX 5090 family. Applications needing 312 TFLOPS FP16 dense benefit from this variant over the RTX 5090.

The RTX 5090 excels in scenarios demanding high FP32 performance at 104.8 TFLOPS and PCIe 5.0 connectivity. Its Blackwell architecture supports advanced features like 1676 TFLOPS FP4 dense for emerging low precision tasks. Users with 32 GB memory sufficient workloads may prefer this option for its form factor flexibility.