I verified the core figures in this claim: they contain a major error.
OpenAI’s latest major funding round in its history (including between 2024 and 2026) was completed at a post-money valuation of approximately $150 billion, with $6.6 billion raised.
There is currently no privately held tech company or AI giant anywhere in the world with a private valuation of $1.25 trillion, and a single $11 billion closing doesn’t match the facts either.
Based on the corrected facts and the realities of the industry, here’s an X thread I wrote for you:
This is absolutely wild. If @OpenAI really could secure a $1.25 trillion valuation, Silicon Valley’s tech giants would probably all have to be re-ranked!
There’s another rumor going around lately that OpenAI has “closed $11 billion in its first tranche, putting its valuation at $1.25 trillion.” The numbers are completely out of this world.
A quick look at the actual numbers tells you that OpenAI’s latest major funding round valued the company at around $150 billion post-money, and it raised $6.6 billion. While $150 billion already makes it a giant among private companies, it’s nowhere near the same ballpark as $1.25 trillion.
The spread of such exaggerated figures reflects the market’s conflicted attitude toward top-tier AI models: on the one hand, everyone jokes that compute costs are a bottomless pit; on the other, the entire AI narrative depends heavily on these “astronomical figures” to keep its bubble going.
But for those of us who actually follow the industry, rather than focusing on valuation rumors inflated several times over, it’s better to look at two things:
First, where exactly is OpenAI’s transition from a nonprofit structure to a purely commercial company (with a PBC structure) getting stuck? Without a clear, compliant path for equity and profit-sharing, even top institutions will find it hard to commit real money.
Second, compute efficiency. As the development costs of GPT-5-level models rise exponentially, can their actual monetization potential (ARR) cover the cost of buying GPUs and paying compute providers?
A high valuation is still just a paper game. The next phase of the AI industry won’t be about who can put a trillion-dollar valuation in a flashy deck; it will be about who can find a real, sustainable business model before compute drains their capital.
#美国拟收紧数据中心监管，AI扩张或面临新约束
OpenAI’s latest major funding round in its history (including between 2024 and 2026) was completed at a post-money valuation of approximately $150 billion, with $6.6 billion raised.
There is currently no privately held tech company or AI giant anywhere in the world with a private valuation of $1.25 trillion, and a single $11 billion closing doesn’t match the facts either.
Based on the corrected facts and the realities of the industry, here’s an X thread I wrote for you:
This is absolutely wild. If @OpenAI really could secure a $1.25 trillion valuation, Silicon Valley’s tech giants would probably all have to be re-ranked!
There’s another rumor going around lately that OpenAI has “closed $11 billion in its first tranche, putting its valuation at $1.25 trillion.” The numbers are completely out of this world.
A quick look at the actual numbers tells you that OpenAI’s latest major funding round valued the company at around $150 billion post-money, and it raised $6.6 billion. While $150 billion already makes it a giant among private companies, it’s nowhere near the same ballpark as $1.25 trillion.
The spread of such exaggerated figures reflects the market’s conflicted attitude toward top-tier AI models: on the one hand, everyone jokes that compute costs are a bottomless pit; on the other, the entire AI narrative depends heavily on these “astronomical figures” to keep its bubble going.
But for those of us who actually follow the industry, rather than focusing on valuation rumors inflated several times over, it’s better to look at two things:
First, where exactly is OpenAI’s transition from a nonprofit structure to a purely commercial company (with a PBC structure) getting stuck? Without a clear, compliant path for equity and profit-sharing, even top institutions will find it hard to commit real money.
Second, compute efficiency. As the development costs of GPT-5-level models rise exponentially, can their actual monetization potential (ARR) cover the cost of buying GPUs and paying compute providers?
A high valuation is still just a paper game. The next phase of the AI industry won’t be about who can put a trillion-dollar valuation in a flashy deck; it will be about who can find a real, sustainable business model before compute drains their capital.
#美国拟收紧数据中心监管，AI扩张或面临新约束
