Zuckerberg Weighed $100 Billion-Plus AI Check After 44-Minute Wang Call

Mark Zuckerberg floated a figure of $100 billion to $200 billion for Meta's AI push during discussions late last year—and he asked Alexandr Wang point-blank whether the plan would hold. "We're going to write this check for like, I don't know, like $100 billion or $200 billion," Zuckerberg said on the latest episode of Cheeky Pint, the podcast hosted by Stripe cofounder John Collison. "I'm like, Alex, you sure this is going to work?"

The number was off the cuff. The scale is not. Meta now expects 2026 capital expenditures of $130 billion to $145 billion, nearly double the $72.2 billion it spent last year—and investors have flinched at each increase.

Wang, the 29-year-old MIT dropout who cofounded Scale AI, got a blunter version of the question from Meta's CFO, Susan Li, at an executive gathering in Hawaii at the end of last year. "Susan pulled me aside many times," Wang said. "I just want to tell you if this doesn't work, this is going to be really, really bad. It's going to be very, very bad in financial terms. I really need to impress on you that this model has to work. It has to be good. If it's good, it's all good. We're great. But if it's bad, it's really, really, really bad."

How did the Zuckerberg-Wang partnership start?

Between sips of Guinness—Zuckerberg's apparent wince went viral—the pair recounted the origins of the deal on the podcast. In April 2025, shortly after Meta's Llama 4 models landed to a lukewarm reception, Zuckerberg started reaching out for advice.

Wang was in a staff meeting when his phone pinged. "I got the WhatsApp notification, like, 'Have time for a call?'" Wang said. "I was like, huh, interesting."

That call ran about 44 minutes, by Zuckerberg's recollection. Two days later, Wang sent a long memo laying out, as Zuckerberg put it, "here's what I think I would do if I were in your position."

The memo's first principle: talent density. "The very first thing is that you don't need a lot of people, and talent density is the thing that matters," Zuckerberg recalled. The second: a willingness to start from scratch. Zuckerberg said Meta was "not happy with the trajectory that we were on with Llama 4," and he was prepared to rebuild the team.

The pick of Wang still raised eyebrows. He had built Scale AI into a data-labeling powerhouse, but as Collison noted, he had never trained a frontier model. Zuckerberg wasn't swayed. "I talked to like all the leaders of all the labs, like all the heads of research," he said. "And I was like, no, Alex is the guy." He added: "It always felt to me like he was the sharpest entrepreneur of his generation, of the ones who I had had a chance to meet."

What did the 'supernova' recruiting push cost?

What followed was a recruiting drive Zuckerberg described as "supernova." The numbers stack up fast:

• Meta paid $14.3 billion for a 49% stake in Scale AI to bring Wang aboard.
• The company reportedly dangled $100 million compensation offers to OpenAI researchers.
• Zuckerberg cleared his calendar for two months. "I don't think either of us slept that much for the first couple of months," he said.

The core research team Wang built inside Meta Superintelligence Labs numbers fewer than 200 people—"closer to 100," Wang said—backed by larger infrastructure and product teams, at a company with roughly 75,000 employees. Wang said he cultivated a culture of "insecure overachievers": researchers who under-promise and over-deliver.

Is the bet paying off?

The output so far includes Muse Spark, the lab's first model, released in April, followed by a string of updates. The Muse consumer app launched in the U.S. on Sept. 8 and became the most popular free app on Apple's App Store, topping 2.5 million downloads in about two weeks, according to Sensor Tower data cited by CNN.

On Monday, Meta released Muse Wonder, its first frontier-class model. Wang said it is state-of-the-art "based on our measurement" for personal and professional agent tasks. Independent scorekeepers are more measured: on Artificial Analysis's Intelligence Index, the flagship Muse Wonder Full lands roughly level with top models from OpenAI and Anthropic but a couple of points behind the leader, according to AI Weekly.

Wang credited Zuckerberg's decisiveness. "Mark has fully internalized power laws in a way that many people have not," he said. "Once he internalizes certain beliefs, the speed and magnitude of willing to change prior actions and pivot towards the worldview that is consistent with those beliefs is pretty unusual."

With capex near $145 billion and a sub-200-person research core, the margin for error at Meta is thin—and by Susan Li's math, a miss would be "really, really, really bad."