OpenAI is reportedly partnering with Broadcom to bring a custom AI accelerator into mass production next year, a move aimed at cost control, supply assurance, and tighter hardware–software integration. The reported partnership points to OpenAI deploying its own chips internally rather than selling them, following the playbooks of Google (TPU), Amazon (Trainium/Inferentia), Microsoft (Maia/Athena), and Meta (MTIA). AI training and inference costs remain stubbornly high as model sizes, context windows, and user demand surge. Custom silicon can shift the cost curve by optimizing for specific workloads, improving energy efficiency, and reducing total cost of ownership across compute, memory, and networking.