Meta postpones Avocado AI model release after failing to match OpenAI and Google benchmarks

Meta Platforms has officially postponed the release of its next-generation artificial intelligence model, codenamed Avocado, following internal testing that revealed the system is unable to match the performance levels set by current industry leaders.[1][2][3] The delay represents a significant strategic setback for the social media giant, which has recently pivoted its entire corporate focus toward achieving what Chief Executive Mark Zuckerberg calls personal superintelligence.[3] Originally slated for a mid-March debut, Avocado is now expected to remain in development until at least May, as Meta engineers struggle to close the widening gap between their proprietary technology and the latest frontier models from Google, OpenAI, and Anthropic.[2]

The decision to hold back the release came after a series of rigorous internal benchmarks focused on complex logical reasoning, advanced software development, and autonomous agentic behavior.[3] While Avocado reportedly showed marked improvement over the company’s previous Llama series and even outperformed Google’s Gemini 2.5 in several categories, it fell short when measured against the state-of-the-art Gemini 3.0 and OpenAI’s GPT-5 variants. Sources familiar with the testing data indicate that Avocado particularly struggled with multi-step planning tasks, a critical component of the emerging agentic AI market where models are expected to execute complex workflows without constant human intervention. In coding and high-level mathematical reasoning, the model also failed to reach the parity required to justify a full-scale commercial launch.

This technical shortfall is occurring against a backdrop of immense financial and organizational pressure. Meta has projected a record capital expenditure of between 115 billion and 135 billion dollars for the current fiscal year, a staggering sum dedicated almost exclusively to AI infrastructure, including the construction of gigawatt-scale data centers and the acquisition of hundreds of thousands of specialized chips. The company’s inability to deliver a frontier-level model despite this unprecedented investment has raised questions among analysts regarding the efficiency of its research and development cycle. The situation is reportedly so critical that senior leadership within Meta’s AI division has discussed the possibility of temporarily licensing Google’s Gemini technology to power the company’s suite of consumer products, a move that would have been unthinkable just a year ago.

The Avocado project marks a fundamental shift in Meta’s philosophy, moving away from the open-source ethos that defined its earlier successes.[3][4][5] For years, Meta was the primary champion of open-weight AI, providing the developer community with the Llama models to foster a decentralized ecosystem. However, under the direction of Alexandr Wang, the founder of Scale AI who was brought in as Meta’s Chief AI Officer following a 14.3 billion dollar investment in his firm, the company has pivoted toward a closed, proprietary model. This shift was driven by concerns over competitive advantage and security, particularly after reports surfaced that international rivals were leveraging Meta’s open-source code to accelerate their own military and industrial AI projects.

This change in direction has not come without internal friction. The move toward closed-source development and the aggressive management style of the new TBD Lab, the elite unit tasked with building Avocado, has led to the departure of several high-profile researchers. Most notably, the exit of long-time chief scientist Yann LeCun, a vocal advocate for open science, signaled a changing of the guard within the company’s hierarchy. Internal memos suggest that while the newer team has achieved remarkable efficiency gains—Avocado is reportedly ten times more compute-efficient than Llama 4—the "reasoning wall" remains a persistent obstacle. The team is now tasked with an intensive two-month "sprint" to refine the model’s post-training and alignment before the new May target.

The implications for the broader AI industry are profound. Meta’s struggle highlights the extreme difficulty of maintaining a seat at the "frontier" table, where the cost of entry is now measured in tens of billions of dollars and progress is increasingly gated by access to high-quality proprietary data and massive compute clusters. If Meta is forced to rely on a competitor's model or settles for a second-tier release, it risks losing the developers and enterprise customers who had previously flocked to its ecosystem. Furthermore, the delay could impact the development of Mango, Meta’s upcoming image and video generation model, which is designed to work in tandem with Avocado to provide a unified multimodal experience across Facebook and Instagram.

Investors have reacted with cautious concern to the news of the delay. While Meta’s core advertising business remains highly profitable, generating enough cash flow to fund these massive AI experiments, the market is becoming less patient with "open-ended" investment cycles. Financial analysts have noted that Meta’s expenses are currently rising faster than its sales, and without a clear breakthrough in AI monetization, the company may face pressure to scale back its ambitious "superintelligence" roadmap. The decision to delay Avocado suggests that Zuckerberg is unwilling to release a product that would be perceived as inferior, preferring to take a hit on the timeline rather than the company’s technical reputation.

As the industry moves toward the latter half of the year, the pressure on Meta will only intensify. Competitors are not standing still; OpenAI is rumored to be readying even more powerful iterations of its "thinking" models, and Anthropic continues to lead in enterprise safety and coding reliability with its Claude 4.5 suite. Meta’s path forward depends entirely on whether the TBD Lab can solve the reasoning deficiencies discovered in Avocado over the next eight weeks. If the May release fails to impress, Meta may find itself relegated to the second tier of AI providers, a position that would fundamentally undermine its multi-billion dollar bet on the future of the digital economy.

The next few months will determine if Meta can truly transform from a social media company into a leader of the artificial intelligence age. The Avocado delay is a sobering reminder that even the deepest pockets cannot always buy a shortcut to scientific breakthroughs. For now, the tech world remains focused on whether Meta’s "personal superintelligence" is a reachable reality or an increasingly expensive aspiration. The company’s ability to eventually ship a model that can truly compete with the giants of the field will be the ultimate test of Zuckerberg’s vision and the technical prowess of his reorganized AI division.