Meta's Behemoth AI Model Delayed Until Fall 2025: Stock Drops as Investors Question $72B AI Investment Strategy

Meta's Behemoth AI Model Faces Significant Delays: What's Happening?

In a significant development for the AI industry, Meta Platforms has pushed back the release of its highly anticipated Behemoth AI model until fall 2025 or possibly later. This delay, reported by The Wall Street Journal on May 15, has sent ripples through the tech world and caused Meta's stock to drop by as much as 3.6% before settling at $643.88, down 2.35% for the day.

The Behemoth model, part of Meta's Llama 4 family of large language models (LLMs), was originally scheduled for release in April 2025 to coincide with Meta's inaugural AI conference for developers, LlamaCon. The company later pushed the internal target to June, but now faces another significant postponement as engineers struggle to make substantial improvements to the model's capabilities.

This setback raises important questions about Meta's ambitious AI strategy and its massive financial investments in the field. The company has committed to spending between $64 billion and $72 billion in capital expenditures this year, with a significant portion allocated to AI development and infrastructure. As the timeline extends further, both internal teams and external investors are beginning to question whether these enormous investments will yield the expected returns.

The Technical Challenges Behind the Delay

According to multiple reports, Meta's engineering teams are facing significant hurdles in enhancing the capabilities of the Behemoth large language model. Internal discussions have centered on whether the improvements over previous iterations are substantial enough to warrant a public release.

In April 2025, Meta described Llama 4 Behemoth as one of the smartest LLMs in the world and our most powerful yet to serve as a teacher for our new models. The company has also publicly claimed that Behemoth outperforms similar models from competitors like Anthropic, Google, and OpenAI on certain benchmarks, including MATH-500 and GPQA Diamond.

However, sources familiar with the matter indicate that Meta's AI engineering and research teams have serious concerns that the new model won't live up to these earlier claims about its capabilities. This disconnect between public statements and internal reality has created tension within the organization and raised questions about the feasibility of Meta's AI roadmap.

It's worth noting that Meta isn't alone in facing such challenges. Other major AI companies have also experienced delays or adjusted expectations for their flagship models. OpenAI initially aimed to launch GPT-5 by mid-2025 but ultimately released that model as GPT-4.5, while Anthropic has delayed the release of its Claude 3.5 Opus model despite earlier claims it was coming soon.

Market Reaction and Financial Implications

The news of Behemoth's delay had an immediate impact on Meta's stock price. Shares fell by as much as 3.6% following the Wall Street Journal report, dropping to as low as $635.58 before recovering slightly to close at $643.88 on May 15, 2025. Despite this setback, Meta's stock is still up approximately 10% year-to-date.

Investors' concerns center around Meta's massive capital expenditure plans for 2025. The company has projected spending between $64 billion and $72 billion this year, with most of that allocated to AI development and infrastructure. These figures represent a significant increase from previous years and reflect CEO Mark Zuckerberg's all-in bet on artificial intelligence as the company's future.

The delay raises questions about whether this enormous investment will generate the expected returns, especially as progress in AI development appears to be slowing across the industry. Some analysts suggest that future advancements may come at a slower pace and potentially cost much more in terms of investment, which could impact Meta's profitability in the coming quarters.

For context, Meta's stock has seen significant volatility in recent months. After reaching highs above $620 in early March 2025, the stock experienced a sharp decline in early April before beginning a recovery. The current uncertainty around its AI strategy adds another layer of complexity for investors trying to evaluate the company's long-term prospects.

Internal Tensions and Management Changes

The postponement of Behemoth has reportedly created internal friction at Meta. According to sources cited by The Wall Street Journal, there is growing disappointment with the team responsible for developing the Llama 4 model, who are being blamed for the lack of progress on Behemoth.

This dissatisfaction has led to discussions about potential significant management changes within Meta's AI product division. The situation highlights the high-pressure environment and enormous stakes involved in the competitive AI landscape, where companies are racing to develop and deploy increasingly sophisticated models.

Adding to the challenges is the fact that most of the researchers who created the original Llama model that debuted in early 2023 are no longer with the company. Of the original team of 14 academics and researchers with doctorate degrees, 11 have since departed. More recent versions of Llama have been developed by an entirely different team, which may have contributed to the current difficulties.

Meta has not publicly committed to a specific timeline for Behemoth's release, giving the company some flexibility. There are indications that Meta might ultimately decide to release the model earlier than currently planned, possibly with a more limited feature set. However, this would represent a significant scaling back of ambitions for what was supposed to be the company's flagship AI offering.

Meta's AI Strategy and Competitive Landscape

The delay of Behemoth comes at a critical time in the AI industry's development. Meta has been praised for its speed in the global AI race, investing tens of billions of dollars in developing technologies to support chatbots on platforms like WhatsApp, Instagram, and Facebook. The company has already integrated AI features across its family of apps, helping users with writing posts and captions, editing images, and more.

In April 2025, Meta released two smaller models from its Llama AI series, Scout and Maverick, and also launched a standalone app for Meta AI. The company also released a hub for its Ray-Ban smart glasses. These initiatives demonstrate Meta's commitment to embedding AI throughout its ecosystem.

However, the reported delay of Behemoth raises concerns that Meta could fall further behind competitors like OpenAI and Google in the race to build advanced AI systems. As Katelyn Chedraoui, a social media and AI reporter who covered LlamaCon in April, noted: The race to build advanced and affordable AI is extremely competitive. The concern for Meta is how far ahead competitors will advance while it's still working on refining the models it has already announced.

This competitive dynamic puts additional pressure on Meta to deliver on its AI promises, especially given the enormous financial resources it has committed to the field. The company's ability to execute its AI strategy effectively will be a key factor in determining its position in the tech landscape in the coming years.

What This Means for the Future of AI Development

Meta's challenges with Behemoth may signal a broader trend in the AI industry. According to experts cited in recent reports, the pace of advancement in AI capabilities may be slowing across all major labs and models.

Ravid Shwartz-Ziv, an assistant professor at New York University's Center for Data Science, observed that The progress is quite small across all the labs, all the models. This suggests that the era of rapid, breakthrough advancements in AI may be giving way to a period of more incremental improvements that require significantly more investment.

This potential slowdown has implications not just for Meta but for the entire tech industry, which has been pouring unprecedented resources into AI development. If the returns on these investments begin to diminish, companies may need to recalibrate their strategies and expectations.

For users of Meta's products, the delay means a longer wait for the enhanced AI capabilities that Behemoth was expected to enable. While Meta continues to roll out AI features across its platforms, the truly transformative advancements that were promised may take longer to materialize.

As of May 16, 2025, Meta has not officially commented on the reported delay. The company's next moves will be closely watched by investors, competitors, and users alike, as they will provide important signals about the future direction of both Meta and the broader AI industry.

Investor Considerations and Future Outlook

For investors in Meta, the delay of Behemoth presents both challenges and opportunities. On one hand, the postponement raises questions about the company's ability to execute on its ambitious AI roadmap and justify its massive capital expenditures. On the other hand, if Meta can eventually deliver a truly superior AI model, it could strengthen its competitive position in the tech ecosystem.

Looking at Meta's recent stock performance provides some context. After closing at $643.88 on May 15, 2025, the stock is still up approximately 10% year-to-date. This suggests that despite short-term volatility, investors maintain a generally positive outlook on the company's prospects.

The broader question for investors is whether Meta's all-in bet on AI will ultimately pay off. CEO Mark Zuckerberg has positioned AI as central to the company's future, integrating it across Meta's family of apps and developing new AI-powered products and services. The success or failure of this strategy will have significant implications for Meta's long-term value.

As the AI landscape continues to evolve, Meta's ability to overcome the current challenges with Behemoth and deliver on its AI promises will be a key factor in determining its position in the tech industry. The coming months will be crucial as the company works to address the technical issues with its flagship AI model and maintain its competitive edge in an increasingly crowded field.