NVIDIA GeForce GTX 1080 Ti 11GB vs NVIDIA P100 SXM2 16GB

The GeForce GTX 1080 Ti is the newer part: Pascal, launched in 2017, against the P100's Pascal from 2016. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.

Dense throughput for the GeForce GTX 1080 Ti against the P100: FP32 11 vs 11 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 11 GB against 16 GB, fed at 484 GB/s versus 732 GB/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 GeForce GTX 1080 Ti and 300 W for the P100. At FP32 that works out to 0.05 against 0.04 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.