B100 vs B200: Which NVIDIA blackwell GPU is right for your AI workloads?
Blog post from Northflank
NVIDIA's B100 and B200 GPUs, based on the Blackwell architecture, offer significant advancements in AI training and inference capabilities, with the B200 introducing improvements in compute density, memory bandwidth, and multi-GPU scaling over its predecessor. While both GPUs share similar memory configurations and NVLink bandwidth, the B200 stands out with higher FP64 compute power and enhanced efficiency, making it ideal for large-scale AI and high-performance computing tasks. The B100 provides balanced performance and is suitable for cost-conscious deployments, whereas the B200 is tailored for maximum throughput and efficiency, especially for handling trillion-parameter models and large language models (LLMs). Despite the B200's higher cost, it offers faster performance and can reduce total workload costs, making it a valuable upgrade for demanding applications. Northflank, a full-stack AI cloud platform, facilitates the deployment of these GPUs, allowing teams to efficiently build, train, and scale their models.