Meta has reportedly delayed the launch of its much-anticipated large language model, Behemoth, pushing the rollout to Fall 2025. Originally scheduled for April and then postponed to June, this second delay is raising eyebrows across the tech world and stirring fresh concerns about Meta’s competitive standing in the rapidly advancing AI industry.

What Is Behemoth?

Behemoth is the latest in Meta’s series of large language models (LLMs) that power various AI experiences across Facebook, Instagram, WhatsApp, and Messenger. Positioned as Meta’s most advanced model to date, Behemoth was described internally as a “teacher model” — one that would guide the training of future, smaller AI systems within its ecosystem.

Despite the buzz, reports suggest Meta engineers believe Behemoth does not significantly outperform the company’s current model, LLaMA 4, which was launched in April. As a result, leadership is choosing to hold off on release until the model is deemed truly competitive and transformative.

Why the Delay Matters

In the high-stakes race for AI dominance, timing is everything. While Meta is taking a more cautious, quality-first approach, competitors like OpenAI, Google, Anthropic, and Microsoft continue to make rapid advancements and release new capabilities to the public at a fast clip.

This delay may hinder Meta’s perceived progress in AI innovation, especially as many other tech giants release cutting-edge models that integrate AI deeper into daily user experiences. Meta has already embedded AI across its products — from auto-captioning and post suggestions to smart replies and image editing — but Behemoth was expected to be a step-change in its capabilities.

If the new model fails to demonstrate significant advantages, it could affect Meta’s momentum and developer interest.

Meta’s AI Vision

Meta has made it clear that artificial intelligence is at the core of its future — powering everything from content discovery and smart messaging to personalized recommendations and AI assistants. The company recently launched a standalone Meta AI app and continues to build integrations into hardware like Ray-Ban smart glasses.

The goal is clear: Meta wants to be a leader in both consumer and enterprise AI. Behemoth, if successful, would serve as the flagship model showcasing Meta’s ability to build scalable, intelligent, and stable systems that rival or surpass today’s best models.

But the repeated delays suggest Meta is still fine-tuning its technology — and perhaps struggling to match the pace set by its competitors.

What's at Stake

Delaying Behemoth might protect Meta from premature criticism, but it also gives rivals more time to leap ahead. In a market where first impressions and speed of deployment matter, Meta’s choice to delay could impact its ability to shape developer trust, business adoption, and public perception.

Investors and AI enthusiasts are now watching closely. Meta’s long-term AI vision depends heavily on models like Behemoth to prove its strength not only in data infrastructure and social platforms — but in fundamental AI capability.

The big question remains: will Behemoth be worth the wait?

Stay tuned for further updates on AI models, releases, and major shifts in the tech ecosystem.