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9.02

Who makes hyperscalers, neoclouds & model labs 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
AlibabaoperatorpublicBABA116 USD-3.6%inferredregion: China and Asia
Alphabet (Google)operatorpublicGOOGLinferred
Amazon (AWS)operatorpublicAMZN256 USD-2.2%inferred
AppleoperatorpublicAAPL315 USD+0.9%inferred
BaiduoperatorpublicBIDU96.94 USD+3.6%inferredregion: China and Asia
KToperatorpublic030200.KS54100 KRW0.0%inferredregion: China and Asia
Meta PlatformsoperatorpublicMETA571 USD-1.4%inferred
MicrosoftoperatorpublicMSFT505 USD+1.8%inferred
Naveroperatorpublic035420.KS220000 KRW+1.6%inferredregion: China and Asia
OracleoperatorpublicORCL152 USD+0.4%inferred
Samsung SDSoperatorpublic018260.KS239000 KRW+2.4%inferredregion: China and Asia
SK Telecomoperatorpublic017670.KS99100 KRW-0.1%inferredregion: China and Asia
Tencentoperatorpublic0700.HK455 HKD+1.6%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
CoreWeaveoperatorpublicCRWV86.80 USD-6.5%inferred
DigitalOceanoperatorpublicDOCN122 USD+3.9%inferred
IRENoperatorpublicIREN40.53 USD-1.0%inferred
NebiusoperatorpublicNBIS218 USD-3.9%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.

Nearby parts

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Google Cloud — hyperscaler tour of an AI-focused data center campus
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Sources: placements without a source URL come from the taxonomy seed and are tagged accordingly. How this data is builtMarkdown · JSON