From Open Source Champion to Closed Source Retreat

Meta's pivot is complete. The company that positioned itself as the champion of open AI—releasing Llama models that powered thousands of startups and research projects—is abandoning open source entirely for 2026. The new proprietary models, codenamed "Mango" and "Avocado," mark the end of an era and the betrayal of a community that built their businesses on Meta's promises.

According to WinBuzzer, Meta is developing two closed-source AI models backed by a $72 billion infrastructure investment. "Mango" will focus on visual media while "Avocado" targets text and code. Neither will be open weights. The Llama lineage is dead.

The Llama 4 Disaster That Broke Everything

The pivot didn't come from strength—it came from failure. Multiple reports detail what went wrong:

• Benchmark Manipulation Scandal: Meta was accused of submitting a special customized model to LM Arena—one that concealed weaknesses compared to the publicly available version. The Llama 4 project became a "data embellishment" scandal

• Behemoth Failure: The Llama 4 "Behemoth" model was postponed due to performance failures, forcing Meta to abandon its flagship release

• DeepSeek Paranoia: Meta's leadership reportedly fears that releasing open weights allows competitors like Chinese lab DeepSeek to clone and optimize Meta's architecture without incurring research costs

• Lukewarm Reception: Despite releasing Scout (109B parameters) and Maverick (400B parameters), market response was "lukewarm" and developer community interest diminished

"The Llama 4 project was exposed as a 'data embellishment' scandal, with former chief scientist Yann LeCun admitting that the team adjusted data to optimize benchmark test results. This behavior sparked controversy, revealing management deviations in Meta's AI technology development." — AI Base News

The Leadership Exodus

The Llama crisis triggered an internal meltdown at Meta:

• Yann LeCun Resignation: Meta's legendary chief AI scientist departed following an October 2025 wave of layoffs targeting the Fundamental AI Research (FAIR) lab

• Chris Cox Removed: Chief Product Officer was stripped of AI oversight following performance issues associated with Llama 4 development

• 600 Staff Laid Off: Infrastructure teams were gutted as cultural clashes intensified between research and product teams

• Cultural Collapse: The combination of leadership departures and layoffs created what insiders describe as a "cultural clash" that accelerated the open source retreat

The "Open Source" Lie Exposed

Even before the pivot, critics questioned whether Llama was ever truly open source. Forkable and other analysts pointed out fundamental problems:

• OSI Rejection: The Open Source Initiative stated that Llama's licenses do not meet The Open Source Definition, which prohibits discrimination against "persons or groups" and "fields of endeavor"

• "Openwashing" Accusation: OSI accused Meta of "openwashing"—claiming open source status without meeting the definition

• Open Weights ≠ Open Source: Llama was always "open weights" with community licenses and conditions, not true open source with full modification and redistribution rights

• Commercial Restrictions: Large companies needed special licensing agreements, undermining the "open" promise

"Meta's new Llama 4 AI models aren't open source—despite what Mark Zuckerberg says. Open-weights models allow downloading model weights under custom licenses, but don't grant the full freedoms of OSI open source." — Forkable

Why Meta Fears Open Source Now

The strategic calculus shifted dramatically in 2025:

• DeepSeek Threat: Chinese lab DeepSeek demonstrated it could take Llama architecture, optimize it significantly, and release competitive models—validating Meta's worst fears about open weights

• Competitive Intelligence: Open weights expose architectural decisions, training methodologies, and capability limits to competitors who can study and surpass them

• Lost Advantage: Once competitors match your architecture, your only advantage becomes compute and data—resources Meta's competitors also have

• No Moat: Open source built community but not competitive moat; Meta concluded it was enabling competitors more than users

The Community Betrayal

Startups and researchers who built on Llama face an uncertain future:

• Migration Pressure: Companies that built Llama into production systems must now evaluate migration to Claude, GPT, or genuinely open alternatives like Mistral

• Trust Destroyed: Meta's pivot validates concerns about building on any single vendor's "open" offerings

• Wasted Investment: Fine-tuning, infrastructure, and tooling built for Llama may not transfer to Mango/Avocado

• Open Source Vacuum: The departure of the highest-profile open AI provider raises questions about the viability of open source AI development

What Replaces Llama

The 2026 landscape for open AI looks different:

• Mistral: The European AI lab remains committed to open weights, though with similar licensing caveats

• DeepSeek: Ironically, the Chinese lab Meta fears has become a genuine open source alternative

• Proprietary Reality: OpenAI, Anthropic, and Google remain closed; Meta's departure leaves Mistral as the only major Western lab with open ambitions

The $72 Billion Gamble

Meta's bet is that proprietary models with massive infrastructure investment can compete with OpenAI and Anthropic directly. The company is essentially admitting that its open source strategy failed to build competitive advantage and is now playing catch-up on a closed playing field where it's years behind.

Whether Mango and Avocado can compete remains uncertain. What's clear is that Meta's "open AI" chapter is closed—and the developers who believed in it are left to rebuild elsewhere.