OpenAI is seeking money at a $1.25 trillion valuation about 11 years after it was founded in December 2015, according to the Financial Times and The Wall Street Journal. Meta, the fastest of the public companies, needed about 17 years to reach a $1 trillion market value, by our count from founding year to milestone.
Anthropic’s Series H round, in May 2026, valued it at $965 billion post-money, about five years after its founding, which leaves it $35 billion short of $1 trillion on that measure.
Short explainer · OpenAI at 11 years vs Meta at 17
A vertical news Short summarising this story. Figures come from the reports of each milestone, the FT and the WSJ; our arithmetic is labelled.
Business Pill · Financial Conditions
An evergreen Business Engineer explainer on how financial conditions shape what companies can raise. It teaches the general idea only and does not discuss these valuations.
The key insight: As we read the reports, OpenAI is seeking a $1.25 trillion valuation about 11 years after its founding, while the fastest public company, Meta, needed about 17 years to reach a $1 trillion market value, by our arithmetic.
The investor Oliver Molander wrote on X that “Microsoft took ~44 years to reach a $1T market cap. Apple took ~42” and that Nvidia “took ~30 years from founding to its first close above $1T”. He added that before Anthropic, OpenAI and SpaceX, “Meta was the quickest at ~17 years”, and that “None of them did it inside a fund life”.
Approximate years from each company’s founding year to its first $1 trillion value, from the reports of each milestone. Teal bars are public market values; ochre bars are private round prices: OpenAI’s reported $1.25 trillion target (a round not yet closed) and Anthropic’s $965 billion Series H, which is below $1 trillion. Years are our arithmetic.
What Was Posted on X
Microsoft took ~44 years to reach a $1T market cap. Apple took ~42. Nvidia, the poster child of the AI boom, took ~30 years from founding to its first close above $1T.
Prior to the AI boom pop-offs like Anthropic, OpenAI and SpaceX, Meta was the quickest at ~17 years.
Oliver Molander’s post on X, 31 October 2026, listing how long Microsoft, Apple, Nvidia and Meta took to reach a $1 trillion market value and noting that none did it inside a fund life. This piece checks those milestones against the reports of the day.
How Long the Public Companies Took
We checked each milestone against the reports of the day. Apple was “the first U.S. company to cross the $1 trillion plateau on Aug. 2, 2018”, 42 years after its founding in 1976. Amazon touched the mark during trading in September 2018 but “was unable to close above the mark”, about 24 years after 1994.
Microsoft first crossed $1 trillion during trading on 25 April 2019 and first closed above it on 30 April, per GeekWire, about 44 years after 1975. Alphabet passed $1 trillion on 16 January 2020, per reports that day, about 21 years after Google’s founding in September 1998.
Facebook, now Meta, passed $1 trillion on 28 June 2021, per CNBC; Bloomberg called it the fastest company to reach the milestone. Tesla followed on 25 October 2021, closing “at just under $1,025 at market close for a valuation of $1.01 trillion”, per Fortune, about 18 years after 2003.
Nvidia touched $1.036 trillion during trading on 30 May 2023 and closed at $990.7 billion that day, per Bloomberg and Yahoo Finance, about 30 years after its founding in 1993. SpaceX priced its IPO at about $1.77 trillion on 12 June 2026 and ended its first day at roughly $2.1 trillion, per Al Jazeera, about 24 years after its founding in 2002.
The Private Marks
OpenAI cut its funding target to about $20 billion at a $1.25 trillion valuation, the FT reported, and the WSJ reported it had raised less than half of its original $30 billion goal. That target comes about 11 years from founding, roughly six years less than Meta’s 17, by our arithmetic; the round had not closed at that valuation when reported.
Anthropic “has raised $65 billion in a Series H funding round, valuing the company at $965 billion post-money”, per reports of its May announcement. PitchBook’s analyst separately values Anthropic at $1.42 trillion, an estimate rather than a price paid. A crypto perpetual contract on Hyperliquid also trades on Anthropic, but it is a synthetic derivative, not a funding round or a market value.
Why the Comparison Is Uneven
A private round price and a public market value are different measures. A round sets the price investors pay for new shares in one deal; a market value applies the last traded price to every share outstanding. The eight public companies averaged 27.5 years from founding to $1 trillion, by our arithmetic.
The Business Lever: Capital Arriving Before the Listing
Molander’s point is about the life of a venture fund: none of the public companies reached $1 trillion inside one. As we read the timeline, Anthropic’s $965 billion round was priced about five years from founding, and OpenAI is seeking a $1.25 trillion valuation about 11 years in, both before any listing.
The Structural Read
As we read Molander’s post, his point is the venture-fund clock: none of the public companies reached $1 trillion inside one fund’s life.
As we read the reports, Anthropic’s Series H priced it at $965 billion post-money about five years in, and PitchBook’s $1.42 trillion is an analyst estimate, not a round.
As we read the milestones, SpaceX passed $1 trillion at its IPO about 24 years after its founding, by our arithmetic, a public listing rather than a private round.
FOR INVESTORSOpenAI is seeking about $20 billion at a $1.25 trillion valuation, per the FT, and had raised less than half of its original $30 billion goal, per the WSJ.
FOR READING THE MILESTONES The eight public companies averaged 27.5 years from founding to $1 trillion, by our arithmetic, from the reports of each milestone.
FOR THE PRIVATE MARKS Anthropic’s $965 billion Series H is $35 billion short of $1 trillion; the Hyperliquid contract on Anthropic is a derivative, not a round or a market value.
The framework notes that of the cloud providers’ revenue backlog, “half of that โ $1.05 trillion โ comes from two cash-burning AI startups, OpenAI and Anthropic.”
As we read it, the framework ties a large share of the cloud backlog to OpenAI and Anthropic, the two companies whose private valuations this piece compares. The framework is the owner’s argument and does not discuss founding-to-trillion timelines.
We count years from founding year to milestone, so each figure is approximate to within a year. OpenAI’s round had not closed at the reported valuation when the WSJ reported it. Founding dates vary by source between incorporation and first operations.
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OpenAI is seeking a $1.25 trillion valuation about 11 years after its founding, against about 17 years for Meta to reach a $1 trillion market value; Anthropic’s Series H, at $965 billion, came about five years in, by our count from the reports cited here.
A note on sourcing. Milestone dates come from contemporaneous reports by Fortune, GeekWire, CNBC, Bloomberg, Yahoo Finance and Al Jazeera; OpenAI figures from the FT and the WSJ; Anthropic’s round from reports of its May announcement. Years from founding are our arithmetic, approximate to within a year. We did not contact the companies.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
