Muse Spark, code-named Avocado, marks the debut of Alexandr Wang's rebuilt AI division — and the end of Meta's Llama-era openness
April 8th, 2026: Muse Spark launches as Meta's first proprietary AI modelNew here? Follow stories to track developments over time. Create a free account to get updates when stories you care about change.
For three years, Meta staked its artificial intelligence strategy on giving models away. The company's Llama series became the most widely used open-weight model family in the industry, downloaded hundreds of millions of times. On April 8, 2026, Meta released Muse Spark — the first model built by its new Superintelligence Labs division — and kept it closed. The shift is not subtle: the company that once argued open-source AI would defeat proprietary rivals the way Linux defeated Unix is now competing on their terms.
Muse Spark is small, fast, and built from scratch under chief AI officer Alexandr Wang, who joined Meta nine months ago after the company spent $14.3 billion to acquire a 49% stake in his former company, Scale AI. The model achieves top scores on health-related benchmarks and competitive results in reasoning and multimodal tasks while using over an order of magnitude less compute than Meta's previous Llama 4 Maverick. But the real story is what it represents: a ground-up rebuild of Meta's AI organization after the Llama 4 launch ended in a benchmark-manipulation scandal that cost Zuckerberg's confidence in his existing AI leadership.
Why it matters
The company that made open-source AI mainstream just went proprietary, reshaping who controls the models billions of people use daily.
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"How like a man to discover the virtues of openness precisely when it stops winning, and the virtues of secrecy precisely when it might."
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Meta's consolidated AI division created after the Llama 4 debacle, replacing the prior GenAI organization and absorbing FAIR's research functions.
The dominant AI data annotation and infrastructure company whose 100,000+ contractors trained models for OpenAI, Google, and Meta — and whose founder Meta effectively acquired for $14.3 billion.
Meta's foundational AI research lab, once a symbol of open-science values and the birthplace of PyTorch, now folded into the proprietary-first Superintelligence Labs.
December 2013 April 2026
Meta Superintelligence Labs debuts its first model — small, fast, and closed-source. It powers the Meta AI app and website, with rollout to WhatsApp, Instagram, Facebook, Messenger, and Ray-Ban glasses planned in coming weeks.
LeCun's startup secures funding at a $3.5 billion valuation, the largest seed round in European history, to build physics-understanding AI systems.
In a Financial Times interview, LeCun confirms that Meta's Llama 4 team used different model variants for different benchmarks to inflate scores.
Meta's founding AI scientist leaves to start AMI Labs, pursuing 'world models' rather than large language models — a philosophical split with Wang's approach.
Restructuring under Wang results in layoffs across Superintelligence Labs, including FAIR researchers, accelerating Yann LeCun's decision to leave.
In a letter on 'personal superintelligence,' Zuckerberg writes Meta must be 'careful about what we choose to open source' — walking back his 2024 position.
Zuckerberg announces MSL with Wang and Nat Friedman as co-leaders, consolidating all AI research and products under one roof.
Meta acquires a 49% non-voting stake in Scale AI and hires its founder as Meta's first-ever chief AI officer.
Meta releases Llama 4 Scout and Maverick. The unusual weekend timing and benchmark irregularities spark immediate controversy.
Alongside the Llama 3.1 release, Zuckerberg publishes a landmark essay arguing open AI will defeat proprietary models like Linux defeated Unix.
Meta releases Llama 2 free for research and commercial use, establishing the open-source AI playbook.
Meta's first large language model debuts with limited access. Weights leak online within a week via 4chan.
Zuckerberg hires Yann LeCun to build FAIR with an open-science mandate, publishing all research publicly.
3 moments from history that rhyme with this story — and how they unfolded.
Google released Android as open source in 2008, rapidly capturing over 70% of the global smartphone market. Once dominance was established, Google progressively moved critical features — maps, messaging, the app store, push notifications — out of the open-source Android Open Source Project and into proprietary Google Play Services. Today, a phone running only open-source Android is functionally unusable for most consumers.
Android's openness attracted manufacturers like Samsung and Huawei, crushing competitors like Windows Phone and BlackBerry.
Google achieved mobile dominance through openness, then locked it in through proprietary services — a pattern now called 'open source as trojan horse.'
Meta used open Llama models to become the default open-weight AI platform, attracting millions of developers. The shift to proprietary Muse follows the same trajectory: use openness to build the ecosystem, then capture value by closing the most capable layer.
Apple's board fired Steve Jobs in 1985 after a power struggle with CEO John Sculley. Jobs founded NeXT, which built technically superior but commercially unsuccessful computers. Twelve years later, Apple — near bankruptcy — acquired NeXT for $427 million and Jobs returned, eventually becoming CEO and transforming the company.
Jobs's departure led to a decade of strategic drift at Apple, while his NeXT work produced the operating system that would become macOS.
The return proved that a company's founding technical vision can survive organizational upheaval if the right leader eventually takes charge.
Meta's AI division experienced its own upheaval: the founding AI leader (LeCun) departed after a new executive (Wang) restructured the organization. LeCun's $1.03 billion AMI Labs venture echoes Jobs's NeXT — a philosophically different approach built outside the mother ship. Whether LeCun's 'world models' or Wang's large language models prove correct is the open question.
HashiCorp, maker of Terraform and other widely used infrastructure tools, switched from the Mozilla Public License to the restrictive Business Source License. The company argued cloud providers were profiting from its open-source work without contributing back. The move immediately prompted the creation of OpenTofu, a community fork, and HashiCorp was later acquired by IBM.
The developer community split: some accepted the new license, others migrated to OpenTofu. Trust in HashiCorp eroded.
HashiCorp's $5.4 billion acquisition by IBM in 2024 suggested the license change was partly an acqui-hire play. The OpenTofu fork survived but never matched Terraform's market share.
Meta faces a similar community fracture risk. Developers who built products on open Llama models now confront a proprietary future. Wang's promise to 'open-source future versions' echoes the qualified assurances other companies made before their open-source shifts became permanent.