Meta, the tech giant known for its ambitious AI projects, has reportedly delayed the launch of its latest AI model, “Behemoth,” amid challenges in improving its performance compared to earlier versions of the Llama model family. Initially scheduled for release during Meta’s first AI developer conference, the rollout has now been postponed, with no clear timeline for its launch. This delay raises concerns not only about the effectiveness of Meta’s AI efforts but also about the pressure to deliver on its massive AI investments. Despite public claims of outperforming its competitors in some benchmarks, internal struggles point to significant obstacles in achieving the desired capabilities for the model, setting the stage for a potential shift in the competitive AI landscape.
Meta’s AI Roadblock: Llama Model Delays and Struggles with Behemoth
Meta’s journey with AI is facing a significant roadblock as the company delays the rollout of its next Llama model, internally known as “Behemoth.” This delay has raised concerns about Meta’s AI strategy and the effectiveness of its investments.
Delay in Behemoth’s Rollout
Originally scheduled for a debut during Meta’s first AI developer conference in April, Behemoth’s release has been pushed to June and potentially postponed until fall 2025. The delay is attributed to difficulties engineers have faced in improving the model’s performance, which has raised internal debate about whether the upgrade is substantial enough to justify its public release.
Shares of Meta (META) have taken a hit, with a 2% decline noted in the stock price by Thursday’s close. Meta’s public claims suggest that Behemoth outperforms competitors such as OpenAI’s models, Google’s offerings, and Anthropic’s AI tools. However, sources within the company have pointed to significant training challenges and doubts about the model’s real-world effectiveness.
Internal Struggles and Industry Pressure
Meta’s initial excitement surrounding the Llama model family was fueled by the company’s ability to catch up to rivals quickly in the generative AI race. However, with the increasing pressure to deliver results, Meta is facing mounting scrutiny from investors, analysts, and its internal team. The company is spending billions on AI development, with plans for up to $65 billion in capital expenditures for 2025, making it imperative for Meta to show tangible progress and ROI.
This is compounded by concerns about whether Meta can meet Wall Street’s expectations and deliver on its promises. The company’s stock price-to-earnings ratio is currently 25.05, meaning investors are paying $25.05 for every dollar of earnings. As Meta grapples with internal AI setbacks, it’s becoming increasingly difficult to signal clear progress.
Compounding Challenges and the Model Benchmark Controversy
Meta’s AI struggles also stem from internal team changes. Many of the key researchers who worked on the first Llama models have left the company. 11 of the 14 original authors have left, shifting leadership and adding to Meta’s AI model development challenges.
Meta admitted to optimizing its AI model for a chatbot leaderboard, sparking controversy over transparency and credibility.
The Larger AI Landscape: Meta Is Not Alone
Meta is not the only company facing delays in AI model releases. OpenAI delayed GPT-5, launching GPT-4.5 instead. Anthropic also postponed Claude 3.5 Opus, though its release is near.
Despite these setbacks, the AI race continues to accelerate, and companies are under intense pressure to innovate, deliver, and set new industry standards.
Conclusion
Meta’s delay in releasing the Behemoth model underscores the complexities involved in pushing AI development forward. Meta faces internal challenges and rising investor pressure, highlighting the tough road AI firms face in meeting big promises.
