Meta Delays Llama4 Release to May, Citing Need for Further Technical Refinement

Meta has decided to postpone the release of its highly anticipated next-generation large language model, Llama4, until at least May, according to insiders. Despite Zuckerberg's repeated high expectations, the development team faced technical hurdles in fine-tuning the base model's performance and optimizing logical reasoning, causing the delay of the original launch plan.
As a cornerstone of Meta's core AI strategy, the development progress of Llama4 directly impacts the company's ability to compete with giants like OpenAI and Google. This delay highlights the growing challenge of balancing computational efficiency with complex instruction-following in top-tier large models. Internal sources indicate that the team is using the extra time for more thorough security stress testing, aiming to deliver a stronger performance in the open-source community.
Despite the delayed release schedule, Meta remains committed to its open-source approach. Llama4 is expected to be available in multiple versions with varying parameter sizes to accommodate diverse inference needs, from mobile devices to enterprise servers. For developers and researchers, the two-month wait could result in more stable productivity outcomes thanks to additional performance refinements.
To support the massive training demands, Meta is continuing to expand its high-end computing clusters. Although the release cycle has been extended, Meta emphasizes that its overall progress in multimodal understanding and long-text processing remains on track. The May launch will serve as a pivotal moment to determine whether Meta can reclaim a top position in the global AI race.
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Meta has decided to postpone the release of its highly anticipated next-generation large language model, Llama4, until at least May, according to insiders. Despite Zuckerberg's repeated high expectations, the development team faced technical hurdles in fine-tuning the base model's performance and optimizing logical reasoning, causing the delay of the original launch plan.
As a cornerstone of Meta's core AI strategy, the development progress of Llama4 directly impacts the company's ability to compete with giants like OpenAI and Google. This delay highlights the growing challenge of balancing computational efficiency with complex instruction-following in top-tier large models. Internal sources indicate that the team is using the extra time for more thorough security stress testing, aiming to deliver a stronger performance in the open-source community.
Despite the delayed release schedule, Meta remains committed to its open-source approach. Llama4 is expected to be available in multiple versions with varying parameter sizes to accommodate diverse inference needs, from mobile devices to enterprise servers. For developers and researchers, the two-month wait could result in more stable productivity outcomes thanks to additional performance refinements.
To support the massive training demands, Meta is continuing to expand its high-end computing clusters. Although the release cycle has been extended, Meta emphasizes that its overall progress in multimodal understanding and long-text processing remains on track. The May launch will serve as a pivotal moment to determine whether Meta can reclaim a top position in the global AI race.
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In 2025, as Sara Du assisted companies in developing MCP servers, a recurring question emerged: how could teams leverage AI agents directly within Slack? The path was obstructed by significant technical barriers, including the complexity of message s
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