The More You Buy, The More You Lose

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The More You Buy, The More You Lose

Ed Zitron<br>Jul 28, 2026<br>29 min read

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If you liked this piece, you should subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5,000 to 18,000 words, including vast, detailed analyses of NVIDIA, Anthropic and OpenAI’s finances, and the AI bubble writ large. My Hater's Guides To the SaaSpocalypse, Private Credit and Private Equity are essential to understanding our current financial system, and my guide to how OpenAI Kills Oracle pairs nicely with my Hater's Guide To Oracle, as well as the Hater’s Guide To Oracle (Part 2).<br>Subscribing to premium is both great value and makes it possible to write these large, deeply-researched free pieces every week.<br>Soundtrack: Queens of the Stone Age — Infinity<br>Two years ago, NVIDIA CEO Jensen Huang said that “the more you buy, the more you save,” referring to its new (at the time) Blackwell GPUs that would “reduce LLM inference operating cost and energy by up to 25x.” Two years later, those supposed gains have been pared back to 10x, based on case studies with private inference providers that do not share their margins and are most-decidedly not profitable, and absolutely nobody seems to mind that NVIDIA overstated the gains on Blackwell (in a vacuum, in specific circumstances) by 150%, partly because these numbers are utterly meaningless, and partly because the media in most cases ardently refuses to criticize this company.<br>Blackwell being “10x better” than Hopper does not appear to have made any AI startups profitable (or even more profitable), it does not appear to have lowered anyone’s costs in a way that we can measure using dollars and cents, and as a result, I feel very little when I’m told that Vera Rubin provides “up to 10x more tokens per megawatt,” especially as that was with DeepSeek R-1, a year-and-a-half-old open source model.<br>Nevertheless, all of this is immaterial to the larger problem that none of this appears to have resulted in anything tangible other than horrendously-overstuffed balance sheets and spuriously-puffed stock prices.<br>Hyperscalers will have sunk over $1.3 trillion dollars into generative AI by the end of 2026, and have plans to spend a trillion dollars more next year. On a very rational level, nothing that large language models (LLMs) have done, do or will do in the future can or will ever bring in the more than $2 trillion (or more) in brand new revenue that will be required to make any of this worth it.<br>To be more specific, between March 2022 and July 2026, Meta, Google, Amazon, and Microsoft added over $850 billion in property, plant, and equipment (PP&E), nearly tripling their PP&E from $498 billion or so, and in a period where they spent over $1 trillion in capital expenditures.<br>In that same four year period, none of them have disclosed their actual revenues from AI or AI-related services, and, as of their latest quarters, capital expenditures now represent 24.4% of Amazon’s, 33.7% of Meta’s, 37.3% of Microsoft’s, and an astonishing 43.4% of Google’s revenue, a number that’s steadily increased over the last three years.<br>They’ve also added over $307 billion in on-balance sheet debt, leaving them with a total of $557 billion, doubled from $250 billion or so in March 2022. I mention on-balance sheet because Nikkei reports that Meta, Google, Amazon and Microsoft have over $1.35 trillion in off-balance sheet debt — either data centers/GPUs yet to be delivered, or debt raised via SPVs that shift the actual “ownership” of them over to another party as a means of making them look less-indebted than they really are.<br>To be clear, it’s totally fine accountancy-wise to not include leases or commitments yet-to-commence, but it’s very important to know how big an anvil hyperscalers are conjuring above their heads. Google, for example, has $811 billion in contracted future spending commitments as of its latest quarter, increasing by a dramatic $661 billion ($478 billion or so in the latest quarter) in the last 6 months, and Meta has over $237 billion in non-cancellable contractual commitments.<br>Over $167 billion of that on-balance sheet debt has been raised in bonds across Google, Meta, and Amazon, with its $25 billion bond sale from July receiving (per Bloomberg) a cool reception, with “demand [settling] at 1.6 times the deal’s size…[and to] put that in perspective, US high-grade corporate deals have seen orders average around four times their size this year.”<br>For some further perspective, per Freedom Broker’s Saken Ismailov, there was around $100 billion of demand for $20bn of Google’s three to fourty-year-long bonds (5x) and around £9.5 billion of demand for its £1 billion 100-year bond sale (9.5x).<br>As of last week, Google’s century bond has already lost 10% of its value.<br>This is a problem, as all four are certain to...