B200 NVL vs TITAN Xp

The B200 NVL's FP16 performance of 4500 TFLOPS dwarfs the TITAN Xp's 12.1 TFLOPS, enabling faster AI training and inference where half-precision dominates: training large models completes over 370 times quicker on the B200 NVL. Its FP32 of 90 TFLOPS still outpaces the TITAN Xp's equal 12.1 TFLOPS in FP16 and FP32, benefiting general compute tasks. FP8 capability at 9000 TFLOPS on the B200 NVL further accelerates quantized inference, absent on the older GPU. Memory bandwidth disparity is stark: 8000 GB/s versus 548 GB/s allows the B200 NVL to handle batch sizes 14 times larger without bottlenecks, crucial for processing massive datasets in deep learning. The 192 GB VRAM versus 12 GB supports models exceeding 100 billion parameters on the B200 NVL, while the TITAN Xp limits users to smaller workloads. Higher TDP of 1000W on the B200 NVL reflects its density, compared to 250W on the TITAN Xp, impacting deployment power budgets.

Select the NVIDIA B200 NVL for large-scale AI training and inference requiring 192 GB VRAM and 4500 TFLOPS FP16 performance. It excels in cloud environments at $10.50 per hour, supporting NVLink for multi-GPU scaling in LLM development or scientific simulations with 8000 GB/s bandwidth for high throughput.

Choose the NVIDIA TITAN Xp for legacy desktop setups or low-power tasks under 250W TDP where 12 GB VRAM suffices. It fits hobbyist gaming, light fine-tuning, or prototyping without cloud costs, given no live rental offers and PCIe compatibility for existing consumer hardware.