The four-category capital scorecard expanded with named transactions, burn-to-revenue context, and a per-category trend across recent issues. Each row corresponds to a row in the summary table on the issue page.
Category
Frontier Labs.
OpenAI, Anthropic, Google DeepMind, xAI
Capital in
~$95B→
vs ~$95B
Revenue out
~$21B→
vs ~$21B
Burn / rev
~1.3x
Lower means more capital out than in.
The read
Frontier labs stayed well-funded and product-led, but W26 did not add a fresh balance-sheet catalyst. Investors should keep watching whether cheaper open and inference-specialist paths force closed labs to adjust pricing before the next major model release.
Trend across recent issues
Capital inRevenue out/$B per issue
Category
Hyperscaler-Hosted.
Azure-OpenAI, AWS-Anthropic, Google Cloud-Gemini, Oracle-OCI
Capital in
~$187B→
vs ~$187B
Revenue out
~$62B→
vs ~$62B
Burn / rev
~3.0x
Lower means more capital out than in.
The read
The hyperscaler-hosted lane remains the largest capital sink, but W26 clarified that the bottlenecks are increasingly supplier allocation and grid access. Buyers should price provider concentration risk into mission-critical inference workloads.
Neocloud capital is shifting toward inference operations rather than only training clusters. Operators should evaluate token latency, geographic placement, and fallback routing across neoclouds instead of treating all GPU capacity as interchangeable.
Enterprise GPU clusters, sovereign and national programs, Cisco / Dell / HPE
Capital in
~$94B→
vs ~$94B
Revenue out
~$36B→
vs ~$36B
Burn / rev
~2.6x
Lower means more capital out than in.
The read
Hybrid and sovereign buyers still need capacity plans that begin with power and grid process, not model choice. FERC's clock creates a late-summer tariff catalyst that could change siting economics across multiple regions.