B300 vs RTX 3080

The FP16 dense performance of 2250 TFLOPS on the B300 exceeds the 59.5 TFLOPS dense FP16 rating on the RTX 3080 by a substantial margin. This delta allows the B300 to complete matrix operations in training and inference workloads at a higher rate than the RTX 3080 when both operate in dense FP16 mode. The FP32 rating of 75 TFLOPS on the B300 versus 29.8 TFLOPS on the RTX 3080 produces a similar advantage for precision sensitive scientific tasks. Memory bandwidth of 8000 GB/s on the B300 compared to 760 GB/s on the RTX 3080 enables larger batch sizes during model execution without memory bottlenecks. The INT8 dense rating of 187.5 TOPS on the B300 sits below the 238 TOPS dense INT8 figure on the RTX 3080 yet the B300 adds FP8 dense at 4500 TFLOPS and FP4 dense at 13500 TFLOPS which remain unavailable on the RTX 3080.

The B300 suits LLM training workloads that require the 262 to 288 GB VRAM capacity and 8000 GB/s bandwidth to handle large models in a single device. Organizations select the B300 for inference tasks that benefit from the 2250 TFLOPS dense FP16 rating and the 1400W TDP power envelope in data center deployments.

The RTX 3080 fits local development environments that operate within the 320W TDP limit and the PCIe form factor. Users choose the RTX 3080 for Stable Diffusion workloads that align with the 10 to 12 GB VRAM and 29.8 TFLOPS FP32 performance in consumer hardware setups.