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North America Internet: Meta Compute Unlocks Capacity (and FCF) for Meta’s Superintelligence Ambitions

Published: 2026-07-01Institution: CitiCompany / ticker: META,GOOGL,AMD,ARM,AVGO,CRWV,NVDAPages: 15Original language: EnglishEvidence page: 1

Research evidence excerpt

North America Internet: Meta Compute Unlocks Capacity (and FCF) for Meta’s Superintelligence Ambitions

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01 Jul 2026 13:05:06 ET │ 15 pages

North America Internet

Meta Compute Unlocks Capacity (and FCF) for Meta's

Superintelligence Ambitions

Ronald Josey AC

CITI'S TAKE +1-212-816-4545

With the potential launch of Meta Compute, per Bloomberg, Meta appears ronald.josey@citi.com

to be planning to offer access to its AI compute and infrastructure, including Tyler Radkethe potential to offer multiple models, similar to AWS’ Bedrock. CEO

Zuckerberg suggested this could be an option at Meta’s annual shareholder +1-415-951-1660

meeting in May and given recent capacity partnerships valued at tyler.radke@citi.com

~$50B/GW, Meta Compute could significantly shore up its FCF while Michael Rollins, CFA

funding its capacity builds (Prometheus and Hyperion DCs) and newer +1-212-816-1116products under MSL. And to this, we continue to expect Meta to launch

multiple new AI products by year-end and has the infrastructure capacity to michael.rollins@citi.com

do so, as Meta Compute becomes a new business unit. In this note, we Heath Terry

include thoughts from Citi’s Software (Tyler Radke) and Telecom (Michael +1-212-723-4624

Rollins) Analysts, whereby they suggest AI demand continues to exceed heath.terry@citi.comsupply despite overcapacity concerns. We reiterate our Buy rating and $850

TP on META. Jamesmichael Sherman-Lewis

+1-415-627-6014

– More Details on Meta Compute: Selling Model Access & Compute Capacity: Per jamesmichael.shermanlewis@citi.com

Bloomberg, Meta is potentially establishing Meta Compute to monetize its AI

infrastructure with plans to sell both model access (including Muse Spark and Jake Hallac, CFA

potentially 3P models) as well as excess GPU compute capacity.

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