Meta Platforms is reportedly nearing the release of Llama 4, the next iteration of its large language model, with a potential launch expected before the end of April, according to a report from The Information.
Highlights
While the release timeline has already seen at least two delays, sources suggest the launch remains tentative and could be postponed again.
The upcoming model reflects Meta’s continued investment in AI development as it competes with industry leaders such as OpenAI and Google in the generative AI space.
The development of Llama 4 comes at a time when major technology companies are under increasing pressure to translate significant AI investments into real-world applications.
Meta, led by CEO Mark Zuckerberg, is projected to spend up to $65 billion in 2025 to strengthen its AI infrastructure—a figure that highlights the company’s expansive commitment to this area.
Performance and Development Challenges
One factor contributing to the delays in Llama 4’s release appears to be performance-related. Internally, the model has reportedly struggled to meet expectations in critical areas such as reasoning and mathematics.
In addition, early evaluations indicated that its capabilities in generating human-like voice interactions were not on par with some of the more recent models from competitors like OpenAI.
In response, Meta’s AI research team has reportedly adjusted the model’s architecture and training strategies to address these shortcomings.
As part of this shift, Meta is said to be drawing from emerging methods used by newer players in the field, including Chinese tech company DeepSeek.
DeepSeek has demonstrated that high-performing models can be developed at lower costs, challenging the notion that only large-scale models deliver top-tier performance.
Llama 4 is expected to incorporate the “mixture of experts” training approach—a technique where different sections of the model specialize in distinct tasks. During inference, only the necessary components are activated, improving both efficiency and computational scalability.
Deployment Strategy and Open-Source Goals
According to internal reports, Meta plans to initially deploy Llama 4 through its virtual assistant, Meta AI, with the possibility of releasing the model as open-source software at a later stage.
This approach mirrors the launch strategy of Llama 3, which debuted in 2023 and offered improved code generation, expanded language support, and more robust mathematical reasoning.
By continuing to embrace open-source principles, Meta aims to make advanced AI tools more accessible to researchers, developers, and startups.
The Llama models have gained traction in the broader AI community for their availability and adaptability, especially for those seeking alternatives to proprietary platforms.
Infrastructure and Investment Highlights
Meta has significantly expanded its computational infrastructure to support Llama 4’s development. The model is being trained on a GPU cluster that includes more than 100,000 Nvidia H100 chips—four times the scale used for Llama 3, which relied on roughly 25,000 chips.
This substantial increase reflects the growing complexity and resource requirements of modern language models.
In addition to its GPU investments, Meta is planning to construct a $10 billion data center in Louisiana as part of its broader AI infrastructure roadmap. The facility is expected to be operational by 2030 and will serve as a key asset in the company’s long-term AI strategy.
Expected Enhancements in Llama 4
While detailed specifications have not been officially released, Llama 4 is expected to deliver improvements across multiple dimensions, including faster performance, enhanced reasoning capabilities, and support for new modalities.
These upgrades are likely to increase the model’s utility across a wide range of applications, from enterprise tools to consumer-facing products.
Since the launch of ChatGPT by OpenAI in late 2022, the AI sector has seen rapid advancement and widespread adoption of generative models.
As companies seek to keep pace with evolving user expectations and enterprise demand, models like Llama 4 are viewed as key indicators of progress.
For Meta, the release of Llama 4 represents not only a technical milestone but also a test of its ability to deliver competitive, scalable AI solutions in a fast-moving market.
While the exact timeline for Llama 4’s release remains uncertain, its anticipated launch will be closely watched as Meta continues to refine its role in the evolving AI ecosystem.
