Meta's 'Behemoth' Llama 4 model might still be months away

Engadget - May 15th, 2025

Last month, Meta hosted its inaugural generative AI conference, LlamaCon, which was expected to feature the release of its ambitious 'Behemoth' Llama 4 model. However, the release has been postponed, initially from April to June and now potentially until fall or later. Meta engineers are reportedly struggling to significantly enhance the model's capabilities, which has led to internal debates about whether the improvements justify a public launch. While Meta has released smaller models like Scout and Maverick, 'Behemoth' is anticipated to have 288 billion active parameters and claims to outperform current leading models on several STEM benchmarks.

The delay in launching 'Behemoth' underscores the pressure Meta faces in the competitive AI landscape, where rapid advancements are crucial. Mark Zuckerberg has made AI a central focus for Meta, with plans to invest up to $72 billion in AI infrastructure this year. Despite these lofty ambitions, the challenges highlight the complexities of developing cutting-edge AI technology. This delay is notable, as it reflects the industry's broader struggles with delivering innovative yet reliable AI models. The outcome of Meta's efforts could significantly impact its standing in the AI race, as well as its financial and strategic goals.

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Story submitted by Fairstory

RATING

6.4

Moderately Fair

Read with skepticism

The article provides a clear and timely overview of Meta's AI development challenges, focusing on the delayed release of the 'Behemoth' Llama 4 model. It effectively communicates key points about Meta's ambitions and investments in AI but lacks depth in terms of source variety and expert analysis. While the topic is of public interest, the article could benefit from a more balanced perspective and greater transparency regarding its sources. The readability and clarity are strong, making it accessible to a wide audience, but the potential for engagement and controversy is limited by the lack of diverse viewpoints and exploration of ethical implications. Overall, the article is informative but could be strengthened by incorporating more comprehensive insights and verification of claims.

Accuracy

The article makes several claims regarding Meta's AI developments, specifically about the 'Behemoth' Llama 4 model. The claim that Meta hosted LlamaCon and planned to release the 'Behemoth' model initially in April is consistent with reported industry events, although exact dates and confirmations from Meta are not specified. The article states that the release has been delayed, citing internal challenges, which aligns with typical industry hurdles but lacks direct confirmation from Meta. The specifications of the 'Behemoth' model, such as having 288 billion parameters and outperforming other AI models, are bold claims that require independent verification or official statements from Meta. Overall, the article provides a plausible overview of Meta's AI ambitions but needs more concrete evidence and direct sources for some of the technical details.

Balance

The article primarily focuses on Meta's challenges and ambitions regarding its AI models, particularly the 'Behemoth' Llama 4. It presents a narrative centered on the company's struggles and delays without exploring broader industry perspectives or competitor responses in depth. While it mentions that Meta is not alone in facing such challenges, it does not provide a comprehensive view of the competitive landscape or alternative viewpoints. The piece could benefit from including insights from AI experts or industry analysts to provide a more balanced perspective on Meta's position within the AI sector.

Clarity

The article is generally clear and concise, with a straightforward narrative structure that makes it easy to follow. It effectively communicates the key points about Meta's AI development challenges and ambitions. However, some technical details, such as the specifications and performance claims of the 'Behemoth' model, could be better explained for readers less familiar with AI technology. Overall, the language is accessible, and the article maintains a neutral tone, aiding comprehension.

Source quality

The article references a report from The Wall Street Journal, which is a reputable source, but does not provide direct quotes or detailed attributions from Meta representatives or other authoritative voices. The reliance on a single secondary source without additional corroboration from primary sources or independent experts limits the depth of the reporting. The absence of direct statements from Meta or AI specialists diminishes the article's credibility and leaves some claims open to question.

Transparency

The article lacks transparency in terms of the methodology used to gather information and the potential biases of the sources referenced. It does not disclose the basis for some of its claims, such as the performance benchmarks of the 'Behemoth' model. Additionally, there is no discussion of potential conflicts of interest or the context in which the information was obtained, which could impact the reader's understanding of the story's impartiality. More explicit details about the sources and the context of the report would enhance transparency.