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$NET's AI hosting is limited by the physics of its edge footprint and by the role of its products. Carrier-hotel sites built for fast network traffic are a different proposition from purpose-built AI datacenters. Cloudflare’s own engineering disclosures acknowledge power constraints, and management distinguishes its strategy from the hyperscalers’ GPU spending race. Our assessment starts with a two-H100-per-server edge configuration. H100 PCIe and NVL-class cards operate around 350–400 watts per GPU, versus up to 700 watts for H100 SXM. Hyperscalers commonly pack eight SXM GPUs into a machine and connect those machines into dense clusters. The distinction is power, cooling, memory bandwidth and GPU interconnects — not simply whether a model can run. The existing edge footprint cannot acquire hyperscaler-class cooling and power density through server upgrades. Dense, liquid-cooled Blackwell and Vera Rubin systems require a different infrastructure commitment. We see little chance that NET’s existing edge footprint becomes a competitive home for those dense clusters. For sustained, large-model inference, our assessment is that sparse edge GPUs cost more per token than dense AI clusters. Geographic proximity saves network transit time, but it does not guarantee a faster first token or a cheaper response. Greater compute capacity, faster interconnects and efficient batching can outweigh the edge’s network advantage. We expect heavy training, frontier-scale hosting and the most demanding next-generation inference to remain concentrated with hyperscalers. Workers AI’s progress with larger open models is real. Hosting those models does not establish an economic advantage over dense clusters. AI Gateway also lets customers route requests to external providers, matching the model and infrastructure to the task. Cloudflare can still win substantially. More agents mean more requests to secure, more Workers executions, more orchestration and more demand for fine-grained access controls. Those workloads build on infrastructure and capabilities Cloudflare already has. On the SaaS Survival Scorecard, we score $NET at 2.5 for Model-Layer Leverage. That reflects its substantial work building an agent harness across inference, orchestration and execution, while stopping short of model post-training and reinforcement learning.

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British American Tobacco: Harvest

British American Tobacco’s U.S. reset revives combustibles and rebuilds its nicotine-pouch portfolio after legacy-brand writedowns and Velo…

BTI $120B
Invariant 5 clicks

Practical Parametric Yield

Cerebras’s WSE-3 faces parametric-yield constraints that could restrict supply, making power and clock-speed tradeoffs central to its next…

CBRS $39B
Irrational Analysis 3 clicks
BTU · long

Peabody Energy Corporation

Peabody Energy, ticker BTU, is a low-cost producer of thermal and metallurgical coal with mines in the United States and Australia.

BTU $3B
Value Investors Club 2 clicks

Nike, Part Two: The Deep Dive

Nike’s second Latticework program examines the company and the global athletic footwear and apparel industry for professional investors.

NKE $51B
Latticework by MOI Global 1 click

Nike, Part One: The Story

Nike grew from a $1,000 shoe-distribution venture in 1964 into the largest sports brand, using athlete endorsements, product innovation and…

NKE $51B
Latticework by MOI Global 2 clicks

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