NVIDIA offers framework for sizing GPUs for AI inference and TCO

NVIDIA's blog presents a practical framework for sizing GPU resources for AI inference workloads, focusing on use case, token patterns, latency targets, concurrency, cache hit rate, model choice, and deployment strategy. It emphasizes core-and-flex capacity planning and model optimization like quantization, pruning, and distillation to lower TCO.