Meta's Avocado AI model signals major pivot from open-source to closed development strategy

Reviewed byNidhi Govil

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Meta is developing Avocado, a closed-source AI model expected to launch in spring 2026, marking a dramatic departure from its open-source Llama approach. The project trains on competitor models including Alibaba's Qwen, Google's Gemma, and OpenAI systems, with CEO Mark Zuckerberg personally overseeing development as the company shifts toward monetizable AI infrastructure.

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Meta's Next AI Model Abandons Open-Source Philosophy

Meta is developing a new AI model code-named Avocado, slated for release in spring 2026, that represents a fundamental strategic shift for the company

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. Unlike the open-source Llama series that defined Meta's AI strategy for years, Avocado will adopt a closed-source model that the company can tightly control and monetize

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. This pivot from open-source to closed proprietary AI models aligns Meta with rivals like Google and OpenAI, marking the biggest departure to date from the philosophy Mark Zuckerberg has championed publicly.

Training With Competitor Models Signals New Approach

The Avocado project is training with competitor models from multiple technology giants, including Alibaba's Qwen, Google's Gemma, and OpenAI's proprietary systems

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. Meta's TBD Lab is using these third-party models as part of the training process, distilling knowledge from rival systems including OpenAI's gpt-oss

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. The incorporation of Chinese technology represents a notable shift in tone for Zuckerberg, who raised concerns on Joe Rogan's podcast in January about Chinese models potentially being shaped by state censorship. While it remains unclear which specific Qwen model was used, the news has drawn significant attention in China, where Qwen had long sought to catch up to Llama

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. The situation now appears reversed, with Qwen serving as a reference point for Llama's successor in model development.

Strategic Shift Follows Llama 4 Disappointment

Meta's strategy shifted dramatically earlier this year after the company released Llama 4, an open-source model that disappointed Silicon Valley and Zuckerberg

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. The CEO sidelined some people who worked on that project and personally recruited top AI researchers and leaders, in some cases offering them hundreds of millions of dollars in multiyear pay packages. Zuckerberg is now personally monitoring the Avocado project's progress and spends much of his time working closely with new hires in the TBD Lab, underscoring the company's high stakes in the next generation of AI

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. Meta's new Chief AI Officer Alexandr Wang, who joined through a $14.3 billion investment deal with his startup Scale AI, is an advocate of closed models

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China's AI Innovation Accelerates Competition

Interest in Chinese open-source models surged in early 2025 with the breakout success of DeepSeek, while both DeepSeek and Qwen have become leading examples of China's rapid AI innovation

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. In November, Alibaba's Qwen3-based app, Qwen Chat, entered public testing and surpassed 10 million downloads within a week, outpacing the initial launches of ChatGPT and DeepSeek. Alibaba aims to position Qianwen as "the gateway to AI-powered daily life," signaling a shift from its traditional enterprise focus toward consumer applications. Nvidia CEO Jensen Huang acknowledged earlier this month that "China is well ahead -- way ahead on open-source," highlighting the competitive pressure facing U.S. companies

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AI Spending Drives Moneymaking AI Model Focus

AI has become Meta's top priority, commanding the bulk of spending and attention from executives as the company races to achieve AI models that can surpass human-level capabilities

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. Zuckerberg has pledged to spend $60 billion on U.S. infrastructure projects over the next three years, most of them AI-related. Meta's AI spending has become the focus of Wall Street investors, who recently balked at Zuckerberg's pledge to continue investing heavily into 2026. While Meta maintains that its AI investments already strengthen the company's advertising business, others have worried that its expensive bet on building data centers and acquiring infrastructure may not contribute to profit for years. The shift to closed development represents an attempt to create direct revenue streams from AI technology, rather than relying solely on indirect benefits to existing products.

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