RTX 5070 Ti vs RTX 5090

The dense FP16 throughput reaches 61.7 TFLOPS on the RTX 5070 Ti and 209.5 TFLOPS on the RTX 5090. This gap indicates that the RTX 5090 processes larger batches during inference and training operations that rely on half precision computations. Memory bandwidth of 672 GB/s versus 1792 GB/s influences the maximum batch sizes feasible without memory swapping. The FP32 figures of 30.9 TFLOPS and 104.8 TFLOPS further separate the two in single precision workloads. The sparse FP16 rating of 123.5 TFLOPS for the RTX 5070 Ti stands against 419 TFLOPS for the RTX 5090. Comparisons must keep dense figures separate from sparse figures to maintain accuracy.

The RTX 5070 Ti variant suits deployments where the 250 W TDP limits total system power draw. Its 16 GB capacity handles moderate model sizes that fit within that memory envelope while the 672 GB/s bandwidth supports standard inference loads. Workloads that prioritize lower energy use over peak throughput select the RTX 5070 Ti variant for sustained operation.

The RTX 5090 variant addresses cases that require the 32 GB capacity to load models exceeding 16 GB. Its 1792 GB/s bandwidth and 104.8 TFLOPS FP32 rating accelerate large batch training and inference. Users needing the 209.5 TFLOPS dense FP16 figure choose the RTX 5090 variant when memory and compute headroom determine feasibility.