9.02

Who makes hyperscalers for AI data centers

Hyperscalers, neoclouds & model labs (the tenants and owners)

The hyperscalers, neoclouds, and AI labs that occupy data center capacity as tenants or owner-operators, and whose capital spending ultimately drives demand for every layer below this one.

These are the buyers: the companies that lease or self-build the buildings from Layer 9.01's developers and REITs, fill them with the compute from Layers 1 through 4, and sell the resulting capacity as cloud services or use it to train and run their own models. The category splits into three tiers with different economics — diversified hyperscalers funding data centers from broad cloud and advertising revenue, neoclouds that are effectively single-purpose GPU-leasing vehicles often financed against the hardware itself, and model labs whose compute is frequently backstopped by a hyperscaler partner or dedicated project financing. This layer doesn't manufacture anything, but it's the layer every other part of the taxonomy is downstream of: capital expenditure guidance from this group is the earliest signal for order books across silicon, networking, power, and construction. For investors, the key distinction is balance-sheet quality and revenue diversity — a hyperscaler's data center spend is one line in a much larger business, while a neocloud's spend is the business, which makes its debt and lease commitments far more sensitive to utilization and to the resale value of GPU generations as they age.

AI delta: AI training and inference workloads are the primary driver of the capital spending that funds every other layer of this taxonomy.

Appears at:Large colo / hyperscale buildingAI campusGW-class campus· cooling:any — Concentrated at hyperscale-building scale and above; individual labs and smaller neoclouds may lease enterprise-scale capacity as well, but the volume that defines this category sits at campus and gigawatt scale.

Companies on this part (18)

CompanyRoleOwnershipTickerPrice1dConfidenceNote
AlibabaoperatorpublicBABA99.64 USD-1.7%inferredregion: China and Asia
Alphabet (Google)operatorpublicGOOGL320 USD-1.3%inferred
Amazon (AWS)operatorpublicAMZN248 USD-1.1%inferred
AppleoperatorpublicAAPL348 USD-0.3%inferred
BaiduoperatorpublicBIDU77.20 USD-0.7%inferredregion: China and Asia
KToperatorpublic030200.KS46800 KRW-1.8%inferredregion: China and Asia
Meta PlatformsoperatorpublicMETA643 USD-0.5%inferred
MicrosoftoperatorpublicMSFT525 USD+0.5%inferred
Naveroperatorpublic035420.KS173600 KRW-1.3%inferredregion: China and Asia
OracleoperatorpublicORCL126 USD+0.8%inferred
Samsung SDSoperatorpublic018260.KS213500 KRW+3.6%inferredregion: China and Asia
SK Telecomoperatorpublic017670.KS74500 KRW-2.1%inferredregion: China and Asia
Tencentoperatorpublic0700.HK386 HKD+0.9%inferredregion: China and Asia
ByteDanceoperatorprivateinferredregion: China and Asia
G42 (Khazna)operatorprivateinferredregion: Gulf
Huaweioperatorprivateinferredregion: China and Asia
Humainoperatorprivateinferredregion: Gulf
Stargate UAEoperatorunknowninferredregion: Gulf

Neoclouds 9.02a

CompanyRoleOwnershipTickerPrice1dConfidenceNote
CoreWeaveoperatorpublicCRWV54.23 USD-0.6%inferred
DigitalOceanoperatorpublicDOCN93.22 USD+1.3%inferred
IRENoperatorpublicIREN24.91 USD-0.9%inferred
NebiusoperatorpublicNBIS159 USD+2.0%inferred
CerebrasoperatorprivateinferredCloud
Crusoeoperatorprivateinferred
Firmus (Sustainable Metal Cloud)operatorprivateinferred
Fluidstackoperatorprivateinferred
GroqoperatorprivateinferredCloud
Lambdaoperatorprivateinferred
Nscaleoperatorprivateinferred
Togetheroperatorprivateinferred
Vultroperatorprivateinferred

Labs 9.02b

CompanyRoleOwnershipTickerPrice1dConfidenceNote
OpenAI · unit of BroadcomoperatorsubsidiaryAVGO*inferred
Anthropicoperatorprivateinferred
Mistraloperatorprivateinferred
xAIoperatorprivateinferred

Who competes here

The same table read the other way: every company above competes for hyperscalers, neoclouds & model labs sockets. Confidence tags matter — an inferred placement is a lead, not a confirmed rivalry.

Seen in real machines

hyperscalers, neoclouds & model labs is named in 1 of the rack teardowns and supercomputer breakdowns on this site. Each line below is a piece of that machine. The companies shown are the ones named on that line, not necessarily the maker of this part.

Nearby parts

From the blog

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AI Hypercomputer: Behind the scenes at a Google Cloud data center
Google Cloud — hyperscaler tour of an AI-focused data center campus
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Questions about hyperscalers, neoclouds & model labs

What are hyperscalers, neoclouds & model labs?
The hyperscalers, neoclouds, and AI labs that occupy data center capacity as tenants or owner-operators, and whose capital spending ultimately drives demand for every layer below this one.
Which companies make hyperscalers for AI data centers?
This catalog lists 18 companies on Hyperscalers, neoclouds & model labs, 13 of them with listed equity: Alibaba, Alphabet (Google), Amazon (AWS), Apple, Baidu, KT, Meta Platforms, Microsoft, Naver, Oracle, and 8 more.
How does AI change demand for hyperscalers, neoclouds & model labs?
AI training and inference workloads are the primary driver of the capital spending that funds every other layer of this taxonomy.
How reliable are these hyperscalers, neoclouds & model labs supplier placements?
The 18 placements on this part break down as 18 inferred. "disclosed" means the company or a filing says so; "reported" comes from trade press or a reference-design list; "inferred" is a taxonomy lead with no citation yet.

Sources: placements without a source URL come from the taxonomy seed and are tagged accordingly. How this data is built.· Markdown · JSON