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Meta targets year end Llama 4.X release
Meta plans a year end rollout of Llama 4.X as it reorganizes AI teams and competes for top talent.

Meta plans to roll out its latest Llama AI model by year end while reorganizing teams and facing staff turnover.
Meta targets year end release for Llama 4.X amid talent churn
Meta is racing to ship Llama 4.X by year end through Meta Superintelligence Labs, specifically a subgroup called TBD. The project aims to produce a production ready version of Llama 4.X, which insiders sometimes refer to as Llama 4.5. The move comes after Meta released Llama 4 models in April, a launch that some developers felt fell short on real world tasks like coding and reasoning. The TBD team is also tasked with reviving the earlier Llama 4 effort and fixing bugs.
Key Takeaways
"We're making good progress towards Llama 4.1 and 4.2, and in parallel, we're also working on our next generation of models that will push the frontier in the next year or so."
Zuckerberg on progress and future priorities for Llama
"training and scaling large models to achieve superintelligence"
MSL leadership on TBD goals and responsibilities
"omni model"
Internal term mentioned in MSL discussions about a broad AI system
The push to move quickly signals Meta’s willingness to bend its structure to speed. Reorganizing AI work around four pillars—training, research, product and infrastructure—shows a company trying to align big ambitions with clearer responsibilities. Yet talent remains a bottleneck. Meta has offered multimillion dollar packages to lure researchers from rivals, a strategy that raises questions about long term costs and loyalty. If the next wave of models stalls or falters, the momentum may be hard to regain.
Highlights
- Meta bets big on talent to move faster than rivals
- Behemoth stays the big unknown in Meta's AI surge
- A startup mindset sits inside a global giant and that is a risk
- If Llama 4.X stalls the plan could lose credibility
Strategic risks from talent churn and aggressive timelines
The drive to release Llama 4.X by year end comes with high staff turnover and aggressive hiring, creating potential delays and budget pressure. Internal documents point to ambitious goals like an omni model, heightening worries about safety, governance, and execution in a fast moving field.
Ambition in AI is growing faster than the systems that govern it.
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