NVIDIA GeForce RTX 4070 SUPER 12GB vs NVIDIA GeForce RTX 4090 D 24GB

The GeForce RTX 4070 SUPER is the newer part: Ada Lovelace, launched in 2024, against the GeForce RTX 4090 D'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 GeForce RTX 4070 SUPER against the GeForce RTX 4090 D: FP64 0.6 vs 1.1 TFLOPS, FP32 35 vs 74 TFLOPS, FP16 71 vs 147 TFLOPS, FP8 142 vs 294 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 12 GB against 24 GB. 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 220 W for the GeForce RTX 4070 SUPER and 425 W for the GeForce RTX 4090 D. At FP32 that works out to 0.16 against 0.17 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.