The Blackwell architecture and B100 GPUs are expected to significantly outperform existing models, leading to early interest from NVIDIA's customers. This high demand within the AI computing sector highlights the ongoing need for more advanced processing capabilities.

The introduction of NVIDIA's B100 products, based on the Blackwell architecture, aims to enhance AI computing performance. The strong market demand indicates that some customers might have already placed pre-orders. NVIDIA faces the challenge of increasing production for its B100 SXM modules, B100 PCIe cards, and DGX servers, due to the new components these products feature.

There are rumors that the Blackwell architecture could incorporate multi-chiplet designs, which might simplify the manufacturing process by improving yields for smaller chips, although assembling multi-chiplet solutions could be complex.

NVIDIA is also developing a variety of products, including the B40 GPU for enterprise and training, and the GB200, combining a B100 GPU with an Arm-based Grace CPU for training large language models. The H200 compute GPU, based on the Hopper architecture, is another addition, enhancing memory capacity and bandwidth for AI and HPC workloads. Despite supply chain optimization efforts, NVIDIA's CEO, Jensen Huang, has acknowledged the difficulty in immediately satisfying the demand for new products.

This potential supply gap for NVIDIA's GPUs could provide an opening for competitors like AMD and Intel, should they manage to deliver competitive alternatives in performance and software support. Both are actively working on their next-gen AI and HPC accelerators.

While initial supply limitations are expected with the launch of NVIDIA's Blackwell-based products, the situation should improve as manufacturing and packaging capacities advance, particularly with developments at TSMC. This evolution is expected to enhance NVIDIA's capacity to meet the demand for its B100 series, gradually shifting focus from the H100 series.