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Sources: OpenAI is telling investors it's targeting ~$600B in total compute spend by 2030, months after Sam Altman touted $1.4T in infrastructure commitments

OpenAI is telling investors that it's now targeting roughly $600 billion in total compute spend by 2030, months …

CNBC

Context & Ripple Effects

OpenAI’s infrastructure push has progressed from early investor discussions around US AI infrastructure to a five-year plan intended to support more than $1 trillion in spending pledges. The newly reported compute target gives investors a more bounded operating-spend figure against that broader commitments narrative.

The target also sits beside OpenAI’s reported revenue ambitions: the company has projected more than $280 billion in 2030 revenue. That makes the financing and monetization path—not compute demand alone—the central test of the plan.

First-order effects

  • OpenAI gives investors a concrete 2030 compute-spending benchmark, sharpening scrutiny of how its capital plan aligns with its previously cited infrastructure commitments.
  • The reported $600 billion target puts more weight on OpenAI’s ability to translate enterprise strategy and consumer ChatGPT revenue into a durable funding base.

Second-order effects

  • Prospective infrastructure financiers and compute partners can use the target as a planning reference, but will likely seek greater clarity on timing, contractual commitments, and OpenAI’s revenue assumptions.
  • Rival AI developers face a clearer signal that access to large-scale compute is becoming a core strategic variable, increasing pressure to secure long-duration capacity and financing.

Third-order effects

  • If comparable plans persist, AI competition will be shaped increasingly by the ability to finance and execute multi-year infrastructure programs, rather than model development alone.
  • The gap between headline infrastructure commitments and funded operating spend may become a key measure of compute execution risk across the sector.

The trend: AI infrastructure is becoming a long-duration financing contest in which compute access, revenue scale, and capital credibility reinforce one another.

Discussion

  • @quinnypig Corey Quinn on x
    As a hyperscale CEO, I'm just going to take a big drink of very hot coffee and read this next article.
  • @teortaxestex @teortaxestex on x
    OpenAI spends *vastly* more on training than on inference. All of their public models released in 2025 couldn't have possibly cost more than ≈$1.5B in training. Concerning. [image]
  • @ethanchoi7 Ethan Choi on x
    @Techmeme Not Techmeme's fault but someone needs to teach CNBC how to math pls. Not a reset - was always $600B in commitments. The $1.4T in commitments was $600B from OpenAI + $800B in capex commitments from their partners. Broke it down here a month ago from publicly available n…
  • @stalkermustang Igor Kotenkov on x
    TLDR Revenue: — OpenAI bumped its 5-year revenue forecast up by ~27%. — Last year's revenue tripled to $13.1B (beating projections by $100M). — New targets: $30B this year, $62B next year. — Consumer sales should double to $17B this year and hit $150B by 2030 (>50% of total
  • @edzitron.com Ed Zitron on bluesky
    Now OpenAI says it will be spending $600bn on compute through 2030, a year when it says it'll make $280bn.  Weirdly it says it made $13.1bn In revenue in 2025, even though Sam Altman said in November it was “way more than that”!  —  www.cnbc.com/2026/02/20/o...  [image]
  • r/StockMarket r on reddit
    OpenAI resets spend expectations, targets around $600 billion by 2030
  • r/technology r on reddit
    OpenAI resets spending expectations, tells investors compute target is around $600 billion by 2030
  • r/technology r on reddit
    OpenAI Forecasts Its Revenue Will Top $280 Billion in 2030
  • r/tech r on reddit
    OpenAI resets spending expectations, tells investors compute target is around $600 billion by 2030