The Neocloud Cartel: How the AI Industry Started Renting Compute From Itself

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TL;DR

The AI industry is increasingly renting compute from a closed network of firms, forming a cartel led by Nvidia. This shift decouples ownership from use, raising concerns about market fragility and control.

Major AI firms are now leasing compute resources from each other, forming a small, interconnected cartel dominated by Nvidia, marking a fundamental shift in how AI infrastructure is accessed and controlled. This development impacts the entire AI industry, as ownership of hardware has become decoupled from its use, concentrating power in a few key players.

Since 2024, the AI industry has relied heavily on a new class of GPU landlords, known as neocloud hyperscalers, such as CoreWeave, Meta, and others, which rent Nvidia hardware to AI labs and companies. In 2026, a notable shift occurred when xAI, a frontier AI lab, leased its supercomputer to competitors like Anthropic and Google, paying over $26 billion annually, despite sitting mostly idle.

This pattern reveals that in 2026, compute resources are increasingly rented from each other rather than owned outright. The financial flows are highly circular, with companies like OpenAI committing over $1.15 trillion in hardware spending, much of which circulates back to Nvidia and other chip suppliers through complex financing arrangements. Nvidia, in particular, holds a dominant position, investing heavily in AI firms and controlling GPU allocation, effectively holding a significant influence over AI compute access.

At a glance
reportWhen: ongoing in 2026, with recent developmen…
The developmentIn 2026, major AI companies began leasing compute resources from each other, creating a tightly interconnected cartel centered around Nvidia’s hardware and financing arrangements.
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The Neocloud Cartel — The Control Series, Part 2: Compute
AI Dispatch · The Control Series · Part 2
Chokepoint 02 — Compute

The Neocloud Cartel

Almost no one racing to build AI owns the machine it runs on. They rent — increasingly from each other — and the money loops back to one chip maker that’s also an investor in nearly everyone at the table.

The loop — money, chips & credits circle a dozen firms
invests ~$100B commits ~$1.15T buy GPUs + equity stakes NVIDIA the chokepoint THE LABS OpenAI · Anthropic CLOUDS & CHIPS CoreWeave·Oracle·AMD ↻ each deal lifts the next one’s value
If it seems circular — it is.
Who actually holds the choke
01 · Upstream
Nvidia takes ~$35B of every $50B/GW
Captures most of every buildout dollar, holds equity in the buyers, and controls chip allocation in a shortage.
02 · The landlords
Rent means someone else’s terms
xAI’s lease reportedly lets Musk reclaim compute if Claude “harms humanity.” CoreWeave drew 77% of revenue from 2 customers.
03 · The financing
Suppliers fund their own buyers
Nvidia invests in OpenAI; AMD hands it warrants; Nvidia+MSFT back Anthropic $15B. The money never leaves the circle.
~$3T
datacenter spend ’25–’28 — half on private credit
−$74B
OpenAI projected operating loss, 2028
~3%
of consumers actually pay for AI
−60–75%
H100 rental rates from peak — commoditizing
The take

The cartel isn’t a conspiracy — it’s the endpoint of extreme capital intensity, real scarcity, and one dominant supplier. But the same circularity that makes it powerful makes it a fuse: each cancelled order is someone else’s missing revenue. Don’t be a price-taker at the bottom of a loop you don’t control — own your inference, keep an open-weight fallback, diversify silicon.

Sources: SpaceX filings; TechCrunch; The Register; Bloomberg; CNBC; Reuters; SemiAnalysis; McKinsey; Morgan Stanley; FT (2025–Jun 2026). Figures are reported commitments, often multi-year, not cash on hand.
thorstenmeyerai.com · 02 / 06

Implications of a Concentrated Compute Cartel in AI

This emerging cartel-like structure means a small group of firms—dominated by Nvidia—controls the critical infrastructure of AI development. Their ability to gate, reprice, or revoke compute access gives them significant influence over the industry’s growth and innovation. However, this tight circularity also introduces potential vulnerabilities: if any link in the chain weakens, the entire system could face disruptions, raising questions about market stability and fairness.

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How the AI Compute Market Became a Closed Loop

Historically, AI companies owned their hardware or leased from general cloud providers. The GPU shortage of 2024-25 prompted a shift towards renting from specialized neocloud hyperscalers like CoreWeave, Meta, and others, which rely primarily on Nvidia chips. By 2026, a new pattern emerged where AI labs like xAI leased their supercomputers to rivals, creating a circular flow of compute resources and financing. Nvidia’s investments and control over chip supply further entrenched its dominance, transforming the compute market into a tightly controlled, interconnected network.

“A gigawatt of AI data center capacity costs roughly $50 billion, with about $35 billion flowing to Nvidia.”

— Jensen Huang, Nvidia CEO

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Unclear Risks and Potential Disruptions in the Compute Cartel

While the structure appears stable, it remains uncertain how vulnerable the system may be if key players like Nvidia encounter supply constraints, regulatory challenges, or shifts in industry dynamics. The potential for disruptions within this circular leasing model is an area for ongoing observation, as is the possibility for new entrants to challenge the current market structure.

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Next Steps for Industry Stability and Competition

Industry analysts anticipate increased attention on Nvidia’s market influence and the circular leasing arrangements. Monitoring supply chain developments, regulatory actions, and strategic shifts among companies will be important. Additionally, technological innovations or alternative hardware sources could influence the future landscape of AI compute infrastructure.

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Key Questions

Why is Nvidia so central to the AI compute market?

Nvidia supplies the majority of GPUs used in AI training and inference, and it controls chip allocation, investments, and financing arrangements, effectively holding a dominant position in AI compute access.

What does it mean for AI companies to rent compute from each other?

Instead of owning hardware, AI companies lease compute resources from specialized providers or directly from each other, creating a circular network that consolidates control and financial flows within the industry.

Could this system be disrupted or broken apart?

The circular leasing model presents potential vulnerabilities. Disruptions in supply, regulatory measures, or technological shifts could impact the stability of this arrangement, but the extent of such risks remains to be seen.

How does this affect innovation in AI?

Concentrated control over compute access may influence the competitive landscape, potentially limiting opportunities for new entrants and affecting the pace of innovation, depending on how access is managed within the network.

Source: ThorstenMeyerAI.com

Nothing in this article is financial or investment advice. Cryptocurrency and precious-metal investments carry significant risk — do your own research and consider a licensed advisor.
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