🤖 AI Summary
Nvidia’s aggressive vendor-financing push — roughly $110B in direct investments (including a $100B, 10-tranche commitment to OpenAI announced Sep 2025) plus another $15B+ in GPU‑backed debt — has rekindled dot‑com-era worries about supplier-funded booms. The OpenAI deal is milestone‑tied and structured as leases (OpenAI’s CFO says most cash flows back to Nvidia); CoreWeave alone carries ~$10.45B of GPU‑collateralized loans and others (e.g., Lambda) add to the nascent GPU‑backed debt market. By one measure Nvidia’s financing equals ~85% of its annual revenue, four times the relative exposure Lucent had in 2000, prompting comparisons to the telecom vendor‑financing playbook that collapsed when demand and liquidity evaporated.
The significance is practical, not just historical: customers are highly concentrated (top 2 account for ~39% of revenue), GPUs are being pledged as multi‑year collateral despite real-world lifespans closer to 1–3 years (vs accounting depreciation stretched to 4–6 years), and SPV structures push infrastructure debt off hyperscalers’ balance sheets. Key risks include GPU utilization vs stockpiling, OpenAI’s path to monetization (it lost $4.7B in H1 2025), potential defaults in the GPU loan market, and hyperscaler moves to custom silicon (Maia, TPU, Trainium) that could erode collateral and demand. That said, hyperscalers remain cash‑rich ($451B operating cash flow in 2024) and AI adoption is real — but the structure and scale of financing merit close monitoring.
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