Anthropic, OpenAI, and SpaceX are bigger than the last 25 years of tech exits

We’ve talked before about the hot IPO summer, but with SpaceX just launched to public markets and Anthropic and (maybe) OpenAI soon to come, it can be easy to miss the sheer scale of what’s happening.

We got a good reminder of it in Wednesday’s NCVA-Pitchbook Venture Monitor report. Not surprisingly, all of the money in private markets is flooding into AI — but one particular figure stood out. Taking the measure of the pending OpenAI and Anthropic IPOs, the report drops this nugget: “Along with the SpaceX IPO, these exits will generate more value than all U.S. VC-backed exits since 2000.”

That’s quite a claim, and when you add up the numbers, it’s hard to disagree. SpaceX has already gone public at a $1.77 trillion valuation, and with both Anthropic and OpenAI pushing into the trillions it’s likely the trio together will land somewhere north of $4 trillion. By comparison, the U.S. Securities and Exchange Commission counted just $70 billion in US-based IPO proceeds last year.

Careful readers will notice a few caveats in the language. It doesn’t include non-U.S. companies like Alibaba, and we’re measuring “value created” as opposed to strictly liquid cash. A lot of the major tech developments happened at companies that had already gone public (the iPhone, the debut of Android, and the launches of YouTube and Instagram), so they wouldn’t be captured in the IPO figures.

Still… that was a pretty eventful 25 years. Among other things, that period saw IPOs from Google (2004), Tesla (2010), and Meta (2012), which are now among the most valuable companies in the world. During the same period, LinkedIn, Slack, and WhatsApp were all acquired for more than $20 billion. Uber’s $84 billion IPO seemed like a lot of money in 2019, but it’s less than 5% of what SpaceX just drummed up.

One factor here is that companies are staying private for longer. The Google of today probably would have delayed its IPO and gone public at a higher number. Another factor is the capital-intensive nature of AI training, which has pushed labs into intense fundraising and inflated valuations. But the sheer scale of the public offerings is still way beyond anything the industry has ever done, and is already pushing the financial infrastructure to its limit.