Nvidia · NVIDIA Blog
Productive, Durable, Fungible: How NVIDIA AI Factories Maximize Return on Investment
Compiled by KHAO Editorial — aggregated from 1 source. See llms.txt for citation guidance.
★ Tier-1 Source
AI factories are built by the megawatt, even by the gigawatt.
Key facts
- The NVIDIA A100 GPU shipped in 2020 and is still in commercial service six years later, demonstrating its continued economic value; CoreWeave recently extended bookings for units first introduced
- SemiAnalysis AgentX data shows NVIDIA Vera Rubin NVL72 systems deliver over 30x higher throughput per megawatt than NVIDIA GB300 NVL72, and up to 45x lower cost per million tokens on the DeepSeek V4
- A September 2026 Sprout analysis, “ The Productive Life of a Data Center GPU,” tracks how that schedule has shifted across every major operator
- Ornn Data finds the market paying 80% as much to rent an A100 GPU on a five-year contract as on a one-month contract
Summary
Earning capacity: What the factory could earn in a year if it sold every token it can produce. Strength cannot fully offset weakness in another. High earning capacity counts for little if the factory sells only part of what it can produce. Engineering codesign across the full stack maximizes AI factory throughput, and continuous software optimization keeps installed hardware productive years after it ships. Power is the binding constraint on an AI factory.