NVIDIA A100 PCIe 40GB vs NVIDIA A100 SXM4 40GB

Both GPUs launched in 2020: the A100 PCIe 40GB on Ampere and the A100 SXM4 40GB on Ampere.

Dense throughput for the A100 PCIe 40GB against the A100 SXM4 40GB: FP64 9.7 vs 9.7 TFLOPS, FP32 20 vs 20 TFLOPS, FP16 312 vs 312 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 40 GB against 40 GB, fed at 1.6 TB/s versus 1.6 TB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.

Power budgets are 250 W for the A100 PCIe 40GB and 400 W for the A100 SXM4 40GB. At FP32 that works out to 0.08 against 0.05 TFLOPS per watt.

For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.