Unlike typical computer hardware that depreciates rapidly, H100 GPUs are trading above their launch price in secondary markets. This market anomaly, driven by the extreme and sustained compute shortage for AI, completely inverts traditional financial models for hardware assets.

AI software is improving so rapidly that older hardware, like a three-year-old NVIDIA inference chip, is now more profitable than it was when new. This phenomenon, where software advancements outpace hardware depreciation, is unprecedented and makes existing infrastructure increasingly valuable.

Despite the rapid pace of hardware innovation, the value of older NVIDIA GPUs like the H100 is holding strong. Cloud provider CoreWeave reports these chips are retaining 90-95% of their pricing power over a 5-6 year lifespan because compute demand far outstrips supply.

Contrary to typical hardware depreciation, GPUs like NVIDIA's H100 are becoming more valuable over time. This is because newer, more efficient AI models can generate significantly more output and value on the same hardware, tying the GPU's worth to its utility rather than its age.

Andreessen highlights a unique economic phenomenon: the pace of AI software improvement outstrips hardware depreciation. This means a three-year-old NVIDIA inference chip can generate more revenue today than when it was new, a complete reversal of typical tech hardware value cycles.

Speechify's CEO reveals that renting a high-end GPU for one year can cost up to 1.5 times its outright purchase price. This makes owning the hardware a significantly better long-term investment, even with depreciation, as older chips can be repurposed for less intensive tasks.

A critical component of NVIDIA's financing initiative is offering residual value guarantees to lenders. NVIDIA guarantees that GPUs will retain a certain rental value after several years, which lowers the underwriting risk for financiers and makes capital cheaper for compute buyers.

Hyperscalers are extending depreciation schedules for AI hardware. While this may look like "cooking the books" to inflate earnings, it's justified by the reality that even 7-8 year old TPUs and GPUs are still running at 100% utilization for less complex AI tasks, making them valuable for longer and validating the accounting change.

Counter to narratives about rapid depreciation, the market for used high-end GPUs is robust. Data from late 2023 showed a second-year H100 reselling for 85 cents on the dollar, and a third-year for 84 cents. This high residual value makes refurbished chips a viable and capital-efficient option for compute providers.