RTX 3080 vs V100

Dense FP16 performance stands at 59.5 TFLOPS for the RTX 3080 and 125 TFLOPS for the V100. Training and inference workloads benefit from the higher dense FP16 rating on the V100 when sparsity remains disabled. The RTX 3080 lists FP16 with sparsity at 119 TFLOPS while the V100 provides no published sparsity value for FP16. Memory bandwidth at 900 GB/s on the V100 surpasses 760 GB/s on the RTX 3080 and thereby enables larger batch sizes during memory bound operations. FP32 at 29.8 TFLOPS on the RTX 3080 exceeds 15.7 TFLOPS on the V100 for workloads that favor single precision throughput.

Choose the RTX 3080 when the whole job fits in 10 to 12 GB, which covers Stable Diffusion, small model inference and LoRA fine tuning of small models. Its 760 GB/s of GDDR6X is only about 16 percent below the V100 at 900 GB/s, so single-card decode speed is close, and its 29.8 TFLOPS of FP32 is nearly double the V100 at 15.7 TFLOPS. It is a PCIe 4.0 consumer card without NVLink, so it is not a multi-GPU training part.

The V100 serves distributed training jobs that exploit 125 TFLOPS dense FP16 and up to 32 GB HBM2 VRAM. NVLink interconnect and 900 GB/s bandwidth accommodate scientific computing workloads that require high memory throughput.