**Gartner’s Neocloud Warning: What Does It Mean for Used Data Center GPU Value?**
Gartner forecasts that more than 80% of neocloud providers could cease independent operations or be acquired by 2030. These companies specialize in renting GPU computing power to AI developers and businesses. Their challenge is significant: massive investments in AI infrastructure must generate enough revenue to cover hardware costs, financing, power, and operations before newer generations of chips make existing equipment less competitive.
Gartner estimates that AI infrastructure spending could reach $7 trillion between 2026 and 2030. However, recovering those investments and generating a reasonable return would require substantially more revenue than Gartner expects the industry to produce. This raises questions about whether every company building AI computing capacity can achieve sustainable economics.
But there is an important distinction between the financial health of GPU cloud providers and the value of the GPUs themselves.
Despite concerns about neocloud profitability, demand for older-generation accelerators remains strong. NVIDIA's H100 rental prices have increased, while one-year H100 contract rates tracked by SemiAnalysis rose from $1.70 per GPU-hour in October 2025 to $2.35 in March 2026, an increase of nearly 40%. Even the A100, launched in 2020, remains in active use, with CoreWeave reporting a contract extending into 2029.
These examples suggest that older GPUs can remain commercially useful long after newer generations arrive. When the latest hardware is expensive or difficult to obtain, businesses may continue using previous-generation accelerators for inference and other workloads.
However, strong rental demand does not automatically guarantee strong resale prices. GPU cloud providers must also cover infrastructure expenses, debt payments, and other operating costs. A company can keep its GPUs busy and still struggle to earn an adequate return on its investment.
There is another potential risk: industry consolidation. If struggling providers sell large quantities of used GPUs to raise cash, the additional supply could put downward pressure on secondhand prices. That remains a possibility rather than an established market trend.
The next major factor to watch is NVIDIA's Vera Rubin generation. As newer systems become more widely available, older GPUs could face greater competition and declining rental rates. Whether this happens quickly will depend on the balance between new computing capacity and continued AI demand.
The key question is not simply whether older GPUs are becoming obsolete. It is whether they can continue generating enough economic value as the AI infrastructure market evolves.
Read the full analysis: https://www.buysellram.com/blog/gartner-neocloud-warning-used-data-center-gpu-value/
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