Meta Platforms Inc., the parent company of Facebook and Instagram, has reportedly postponed the public release of its much-anticipated artificial intelligence model, codenamed "Behemoth." According to individuals familiar with the matter, the decision reflects a broader recalibration of the company's AI roadmap rather than any technical shortcoming.

The delay comes as Meta intensifies internal testing and reassessment of Behemoth’s deployment strategy, aiming to better align the advanced model with its long-term goals in AI safety, monetization, and competition with rivals like OpenAI, Google DeepMind, and Anthropic.

A Goliath in the Making

Behemoth was initially touted as Meta’s most powerful language model to date — potentially surpassing the capabilities of its existing LLaMA (Large Language Model Meta AI) models. Insiders describe it as a cutting-edge, multi-trillion parameter system designed to power a range of generative AI tools, from conversational agents to creative content generation, and enterprise applications.

Leaked benchmarks suggested that Behemoth could rival OpenAI’s GPT-5 in both performance and versatility. The model was expected to be open-sourced in part, continuing Meta's strategy of releasing foundational AI models to the research community, albeit with certain limitations.

Why the Delay?

Sources indicate that the delay stems from a combination of factors:

• Safety Concerns: Internal safety reviews reportedly flagged the need for more rigorous guardrails. Meta has been under pressure to prevent misuse of its AI models, especially after prior incidents where released models were used to generate misleading or harmful content.

• Strategic Realignment: CEO Mark Zuckerberg has reportedly instructed AI teams to prioritize product integration over open-source distribution. The goal is to ensure Meta’s consumer-facing platforms, including Facebook, Instagram, and WhatsApp, benefit directly from in-house AI innovations before broader external access is granted.

• Infrastructure Readiness: Deploying a model as large and complex as Behemoth requires extensive computing resources. While Meta has invested billions into building AI-specific infrastructure, some insiders say additional scaling and optimization are needed to support widespread deployment.

Industry Implications

The postponement of Behemoth's release marks a notable moment in the ongoing AI arms race among tech giants. While Meta has been lauded for its transparency in AI research, this shift hints at a more protective posture as competition heats up.

“Open-sourcing is no longer a given,” said one AI researcher familiar with the industry. “These companies are realizing that their models are not just research tools — they’re potential platforms for trillion-dollar ecosystems.”

What’s Next?

Though a new release timeline for Behemoth has not been officially announced, Meta is expected to provide updates at its upcoming developer conference later this year. In the meantime, the company continues to push forward with LLaMA 3 and a suite of AI-powered features across its apps, including image generation, smart assistants, and content moderation tools.

Observers say the delay may ultimately reflect a more cautious and deliberate approach to AI — one that balances innovation with responsibility.