Llama 4s Hype Meets Development Reality | Generated by AI
Understanding the Llama 4 Trajectory and Zuckerberg’s Comments
Mark Zuckerberg initially hyped Llama 4 as a major leap forward for Meta’s open-source AI efforts, with multiple releases planned throughout 2025 to drive advancements in multimodal capabilities (like handling text and images natively). In a December 2024 update, he teased it as the “next stop” after Llama 3, and by April 2025, Meta rolled out the first parts of the “Llama 4 herd”—smaller models like Llama 4 Scout (optimized for speed on a single GPU) and Llama 4 Maverick (for longer context handling). Zuckerberg celebrated this in a video, saying the “trajectory here is clear” and more drops were coming soon.
However, things didn’t pan out as smoothly for the full Llama 4 lineup, especially the flagship “Behemoth” model (a massive 2-trillion-parameter beast). By May 2025, reports emerged that Meta was delaying Behemoth’s release due to internal concerns: engineers were struggling to make meaningful performance gains over prior versions, and there were doubts about whether the improvements were substantial enough to warrant a public launch. This put the project off the aggressive timeline Zuckerberg had outlined earlier, where he pushed teams hard in early 2025 to hit key milestones within about 48 weeks.
Fast-forward to July 2025, and things escalated—Meta reportedly considered abandoning Behemoth altogether after training wrapped up, citing “poor internal performance.” They halted further testing and shifted focus toward a new closed-source model instead of sticking with the open-source path. This pivot aligned with Zuckerberg’s September 2025 comments, where he admitted Llama 4 “was not on the right trajectory,” prompting a major hiring push for a “superintelligence lab” at Meta to regroup and accelerate progress without rigid top-down deadlines.
As of October 2025, the core Llama 4 releases (Scout and Maverick) are out and available (even on platforms like AWS), but Behemoth remains unreleased and effectively shelved. The core issue boils down to underwhelming results during development—not hitting the performance benchmarks needed to compete with rivals like OpenAI or Google, despite massive compute investments. Zuckerberg’s optimism early on clashed with these realities, leading to delays, resource reallocation, and a strategic rethink toward more controlled (closed-source) development.
In short, it’s a classic case of AI hype meeting the grind of scaling: ambitious goals, but technical hurdles in squeezing out those last bits of capability from ever-larger models.
References
- Mark Zuckerberg on Llama 4 Training Progress
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[Llama 4 is here Mark Zuckerberg](https://www.facebook.com/zuck/videos/llama-4-is-here-/1334337587862376/) - The future of AI: Built with Llama
- Zuckerberg Says His AI Lab Is ‘Very Flat’ With No Top-Down Deadlines
- Meta delays release of its ‘Behemoth’ AI model, WSJ reports
- Meta Plans to Abandon Llama 4 Behemoth. But Why?
- The Llama 4 herd: The beginning of a new era