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

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TL;DR

AI industry heavily relies on renting GPU compute from a small, interconnected group of firms, forming a cartel centered around Nvidia. This control influences costs and market dynamics but also introduces fragility.

In 2026, the AI industry has shifted to a model where most companies rent their compute resources from a tightly interconnected group of firms, primarily Nvidia, effectively creating a cartel that controls access and pricing. This development is confirmed by industry sources and recent market analyses, indicating a significant change in how AI companies acquire the hardware necessary for training large models.

Almost none of the leading AI firms own their hardware; instead, they rent from a small group of GPU landlords, including CoreWeave, xAI, and others, who in turn are heavily financed and interconnected. Notably, xAI leased its Colossus 1 supercomputer to Anthropic and Google, paying over $26 billion annually, illustrating how ownership has decoupled from use.

This circular rental system is underpinned by a small number of key players, with Nvidia emerging as the dominant force, capturing the majority of the revenue and controlling GPU allocations. Nvidia has invested heavily in both hardware and financial arrangements, effectively becoming the gatekeeper of the compute supply chain. Major firms like OpenAI, Meta, and others have committed hundreds of billions of dollars to this ecosystem, often backed by Nvidia and other suppliers.

At a glance
reportWhen: ongoing, with developments ongoing thro…
The developmentIn 2026, a small group of AI firms and chip suppliers are engaging in circular compute rentals, effectively forming a cartel that controls access to GPU resources.
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 the AI Compute Cartel

This structure gives a handful of firms, especially Nvidia, outsized control over the AI industry’s core resource—compute power. Their ability to allocate, reprice, or revoke access directly impacts AI development, costs, and competition. While this concentration boosts efficiency and capital flow, it also introduces risks of fragility, as the entire system depends on a small circle of interconnected firms whose financial and operational health are tightly linked.

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GPU cloud computing services

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Background on the Rise of the Neocloud

In response to the 2024–25 GPU shortage, AI firms shifted from owning hardware to renting, leading to the emergence of the ‘neocloud’—a new hyperscaler model focused solely on AI compute. CoreWeave, Meta, OpenAI, and others rapidly expanded their rental agreements, with Nvidia becoming the central supplier and financier. The industry’s move to circular financing and leasing has transformed the compute layer into a tightly controlled cartel, with a few firms holding most of the power.

“The cost of a gigawatt of AI data center capacity is roughly $50 billion, with most flowing to Nvidia.”

— Nvidia CEO Jensen Huang

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AI training hardware rental

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Unclear Aspects of the Compute Cartel’s Stability

It remains uncertain how fragile this cartel is long-term, given its reliance on circular financing and a few key players. The potential for disruption or regulatory intervention could challenge the current structure, but specific vulnerabilities have not yet been fully analyzed or tested.

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Nvidia GPU server rental

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Future Developments in AI Compute Control

Expect continued consolidation among major firms, with Nvidia likely maintaining its dominant position. Regulatory scrutiny may increase, potentially challenging the cartel’s structure. Additionally, new hardware innovations or alternative architectures could disrupt the current leasing and ownership model.

Amazon

supercomputer leasing for AI

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Key Questions

What is the neocloud?

The neocloud is a term for AI-focused hyperscale compute providers that rent GPU resources from each other, forming a tightly interconnected ecosystem centered around Nvidia.

Why does Nvidia dominate AI compute?

Nvidia controls most of the GPU supply, has invested heavily in financing arrangements, and holds key market share, making it the gatekeeper of AI hardware access.

What risks does this compute cartel face?

The cartel’s reliance on circular financing, limited competition, and potential regulatory intervention could threaten its stability and lead to market disruptions.

How does this affect AI development?

Control over compute access influences costs, development timelines, and competitive dynamics, potentially centralizing power among a few firms.

Source: ThorstenMeyerAI.com

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