NVIDIA GeForce RTX 2060 Super 8GB vs NVIDIA GeForce RTX 2080 Ti 11GB

The GeForce RTX 2060 Super is the newer part: Turing, launched in 2019, against the GeForce RTX 2080 Ti's Turing from 2018. 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 RTX 2060 Super against the GeForce RTX 2080 Ti: FP64 0.2 vs 0.4 TFLOPS, FP32 7.2 vs 14 TFLOPS, FP16 29 vs 57 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 8 GB against 11 GB, fed at 448 GB/s versus 616 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 175 W for the GeForce RTX 2060 Super and 260 W for the GeForce RTX 2080 Ti. At FP32 that works out to 0.04 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.