NVIDIA RTX 6000 Ada 48GB vs NVIDIA L20 48GB

The L20 is the newer part: Ada Lovelace, launched in 2024, against the RTX 6000 Ada's Ada Lovelace from 2023. 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 RTX 6000 Ada against the L20: FP32 91 vs 60 TFLOPS, FP8 729 vs 239 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 48 GB against 48 GB, fed at 960 GB/s versus 864 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 300 W for the RTX 6000 Ada and 275 W for the L20. At FP32 that works out to 0.30 against 0.22 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.