The company hopes to raise as much as $90.4 billion, with a base offering of $64.4 billion and a $26 billion private placement, the filing showed.
The company is selling shares for $70 to $78 each, with 801.4 million shares from Anthropic itself and 23.6 million shares coming from stockholders. The $1.4 trillion is lower than the $2 trillion investors had anticipated earlier this year.
Anthropic was preparing to begin formal marketing of its IPO as soon as Tuesday, Bloomberg reported Monday (Nov. 9), pointing out some “last-minute drama” involving a filing mishap ahead of the listing. The hiccup happened Monday when a leaked prospectus mistakenly showed a $69.3 billion fundraising target before being retracted, in what Bloomberg described as an “unexpected jolt to investors” preparing for the IPO.
The figure, which Anthropic has since said was outdated, showed a target that would fall short of a previous goal of matching SpaceX’s record market listing, the report said.
A separate report from The Information said the retracted document was an updated prospectus from the company’s outside counsel in Canada. The counsel later told the banks that received the document that some of the details were not accurate and it would update the filing.
Anthropic is expected to launch its investor roadshow to market the IPO Tuesday and could start trading as soon as Nov. 19, according to The Information.
Anthropic needs to convince investors this is the right time to list amid a downturn in AI stocks, the Bloomberg report said.
Meanwhile, Anthropic launched its Fable 5.2 and Mythos 5.2 AI models Monday, the same day as Meta’s new Muse Ember, PYMNTS reported. These releases bring renewed focus on the safety challenges that come with increasingly capable AI models.
Anthropic said it subjected the new models to lengthy periods of testing and additional evaluations, and the latest versions are less likely to breach the confines of testing environments than their predecessors.
“For both companies, the announcements underscore a market focused on making AI agents practical for business use,” the report said. “Greater reasoning capabilities remain important, but cost, speed and the ability to execute complex workflows are becoming equally significant measures of competitiveness.”
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