Meta delays its flagship model and weighs licensing Google's technology as rivals pull ahead
March 13th, 2026: Avocado delayed to May; Google Gemini licensing discussedNew here? Follow stories to track developments over time. Create a free account to get updates when stories you care about change.
Meta Platforms has committed more money to artificial intelligence than any other company in history—up to $135 billion in 2026 alone, and $600 billion in American data center infrastructure by 2028. But money hasn't bought capability. The company's next-generation AI model, code-named Avocado, was delayed from March to at least May 2026 after tests showed it trailing Google, OpenAI, and Anthropic on reasoning, coding, and writing.
The shortfall has pushed Meta to consider temporarily licensing Google's Gemini to power Meta AI across Facebook, Instagram, and WhatsApp. For a company that abandoned open-source Llama for proprietary development and spent $14.3 billion on a new AI chief, this move exposes the central tension. Building data centers has known solutions; building frontier models has none.
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Curated perspectives — historical figures and your fellow readers.
Fictional AI pastiche — not real quote.
"They spent six hundred billion dollars to discover what every writer has always known: you cannot buy the muse, only the desk she refuses to sit at."
Fictional AI pastiche — not real quote.
"Aye, Mr. Zuckerberg has learned what every steelman knows: you can buy a furnace, but you cannot buy the knowledge of how to run it — and six hundred billion dollars' worth of brick and iron is worthless without the men of genius to light the fire within."
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Parent company of Facebook, Instagram, and WhatsApp, now spending more on AI development than any other corporation.
Meta's consolidated AI division, formed by merging its generative AI, Llama, and product teams under a single mandate to build superintelligence.
April 2025 March 2026
Internal testing showed Avocado trailing Google, OpenAI, and Anthropic models on reasoning, coding, and writing. Meta pushed the launch from March to at least May. Leadership discussed temporarily licensing Google's Gemini to power Meta AI products. Meta shares fell 4.5%, the steepest drop in over four months.
Google released Gemini 3.1 Pro with a 77.1% score on the ARC-AGI-2 benchmark—more than doubling its predecessor. Combined with strong releases from OpenAI and Anthropic in February, the competitive bar rose sharply just as Meta was finalizing Avocado.
Meta announced 2026 capital expenditure guidance of $115–135 billion, nearly double the prior year. Chief financial officer Susan Li said the company remained "capacity constrained" and that compute demand was growing faster than supply.
Reports confirmed that Meta's next flagship AI model, code-named Avocado, would be closed-source and proprietary—abandoning the open-weight philosophy that had defined the Llama series and attracted a large developer community.
LeCun, a Turing Award winner who founded Meta's AI research lab 12 years earlier, confirmed he would leave to build Advanced Machine Intelligence Labs, a startup pursuing a fundamentally different approach to AI.
After years of championing open-source AI models, Zuckerberg said Meta would likely not open-source all of its superintelligence models, citing competitive and security concerns—partly driven by Chinese firm DeepSeek's use of Llama's architecture.
Zuckerberg announced the creation of Meta Superintelligence Labs in an internal memo, consolidating the company's AI research, model development, and product teams under a single division led by Wang.
Meta acquired a 49% nonvoting stake in Scale AI and recruited its 28-year-old founder Alexandr Wang as Meta's first chief AI officer, making him one of the highest-paid employees in the technology industry.
Chief product officer Chris Cox restructured Meta's AI teams into an AI Products group (led by Connor Hayes) and an AGI Foundations unit (co-led by Ahmad Al-Dahle and Amir Frenkel) to speed product development.
Meta's largest planned model, Llama 4 Behemoth, was pushed from early summer to fall 2025 or later. Engineers grappled with whether its improvements over earlier versions justified a public release. The model was eventually shelved.
Meta released Llama 4 Scout and Maverick, but the launch was overshadowed by accusations that a specially crafted, unreleased variant had been submitted to the LM Arena benchmark to inflate scores. Meta denied the claims.
Joelle Pineau, vice president of AI research who led Meta's Fundamental AI Research lab since 2023, announced she would leave the company. She later joined Cohere as chief AI officer.
3 moments from history that rhyme with this story — and how they unfolded.
In June 2000, Yahoo replaced its in-house search technology with Google's engine, making Google the system powering Yahoo's search results. The deal gave Google a "Powered by Google" credit on one of the internet's most-visited pages, exposing millions of users to the Google brand for the first time.
Yahoo got a better search product and could focus on media and content. Google gained massive visibility and traffic.
Google used the exposure to build its own destination site, launched AdWords, and became the dominant search engine. When Yahoo ended the deal in 2004 and built its own search, it was too late to reclaim the market.
If Meta licenses Gemini, it risks a similar dynamic: Google gains public validation that its AI model is superior enough for a competitor to pay for, while Meta's own brand becomes associated with someone else's technology. The longer the licensing lasts, the harder it becomes to justify switching back.
Apple had built its Mac identity around PowerPC chips developed with partners IBM and Motorola. When those partners failed to deliver processors competitive with Intel's x86 chips—particularly on laptop power efficiency—Steve Jobs announced at the 2005 Worldwide Developers Conference that all Macs would transition to Intel hardware, a move many considered unthinkable.
Mac performance improved significantly, and the transition was completed faster than expected. Developers adapted within two years.
Apple treated Intel as a bridge, not a destination. It quietly developed its own ARM-based chips and in 2020 launched Apple Silicon, leaving Intel behind entirely. The interim dependency funded the time needed to build a superior alternative.
Meta's potential Gemini licensing could serve a similar bridge function—buying time to improve Avocado without shipping an inferior product. The question is whether Meta, like Apple, treats the dependency as temporary and invests in catching up, or whether it becomes a crutch.
IBM, the dominant computer company, needed an operating system for its new Personal Computer and licensed DOS from a small company called Microsoft rather than building its own. IBM believed hardware was the real competitive advantage and that the operating system was a commodity component. The deal gave Microsoft the right to license DOS to other manufacturers.
IBM shipped the PC on schedule and dominated the early personal computer market.
Clone manufacturers used the same Intel chips and Microsoft software to build cheaper alternatives. IBM's hardware advantage eroded, and Microsoft's Windows became the industry's true platform. Microsoft eventually became the world's most valuable company.
Meta's $600 billion infrastructure bet assumes data centers and compute are the durable competitive advantage. But if the AI model—the software layer—is where differentiation actually lives, Meta risks building enormously expensive infrastructure that any capable model provider could theoretically run on. The IBM precedent suggests that the company controlling the software platform, not the hardware, often captures the most value.