Is Behemoth Too Big to Succeed? Meta’s AI Delays Expose Industry-Wide Growing Pains

Meta’s flagship AI model, Behemoth, is stuck in limbo—and it’s not just about missed deadlines. The company has delayed its "smartest LLM in the world" twice this year, pushing its launch to fall 2025 amid performance concerns and technical struggles. With rivals like OpenAI and Google racing ahead, can Meta’s ambitious AI vision survive its own hype? Let’s dive in.

🤖 The Behemoth Dilemma: Why Can’t Meta Tame Its AI?

• Three Strikes: Originally slated for April, then June, Behemoth’s launch is now delayed until at least fall—a clear sign of internal turbulence.
• Performance Anxiety: Meta reportedly fears Behemoth may not live up to its public claims of outperforming Anthropic’s Claude 3, Google’s Gemini, and OpenAI’s GPT-5 in key benchmarks.
• Open-Source Contradiction: While promoting Llama 4 Scout and Maverick as cost-effective alternatives to closed models, Meta’s own flagship product remains under wraps.

✅ Meta’s Counterattack: Throwing Billions at the Problem

• 💰 $72B Bet: Meta plans to spend up to $72 billion on AI infrastructure in 2025—a $7 billion increase from earlier projections—to build data centers capable of training Behemoth.
• Teacher Model Strategy: Behemoth is designed to act as a "teacher" for smaller, more efficient AI models like Llama 4, potentially democratizing AI development.
• Zuckerberg’s Vision: "The opportunities ahead are staggering," the CEO declared, framing delays as necessary for long-term dominance.

⚠️ The AI Arms Race’s Hidden Costs

• 🚧 Technical Debt: Building models at Behemoth’s scale requires unprecedented computational power—even Meta’s vast infrastructure is straining under the load.
• ⚡ Energy Hunger: Training such models could consume energy equivalent to powering small cities, raising sustainability concerns.
• 🤼♂️ Competitive Pressure: With OpenAI reportedly testing GPT-5 and Google accelerating Gemini updates, Meta risks losing developer mindshare.

🚀 Final Thoughts: A Make-or-Break Moment for Open-Source AI

Meta’s delays reveal a harsh truth: even tech giants struggle to balance AI ambition with execution. Success hinges on:

• 📈 Delivering Real Benchmarks: Behemoth needs to prove it’s not just bigger, but smarter than closed models.
• 🌍 Sustainable Scaling: Can Meta’s infrastructure handle Behemoth’s demands without environmental blowback?
• 🤝 Developer Trust: Will open-source advocates stick with Llama if Behemoth keeps missing deadlines?

As Zuckerberg bets the farm on AI, one question looms: Is building bigger models the future—or a dead end? What do you think?

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Sources: PYMNTS. Report: Meta Delays Rollout of Behemoth AI Model Amid Performance Concerns, May 15, 2025. https://www.pymnts.com/news/artificial-intelligence/2025/meta-delays-rollout-behemoth-ai-model-amid-performance-concerns/