- Llama 4 introduces multimodal models capable of understanding text and images.
- Scout and Maverick are now available and outperform models like GPT-4o and Gemini 2.0.
- Behemoth, with 2 trillion total parameters, will be Meta's most powerful model.
Meta has once again revolutionized the landscape of Artificial Intelligence with the announcement of its new generation of models, Llama 4, composed of the versions Scout, Maverick and Behemoth. These models not only consolidate the company's strategy to lead the development of IA open, but also set a new standard in terms of efficiency, multimodal capabilities and flexibility in real-world applications.
With this new family, Meta brings to the table the possibility of creating virtual assistants and intelligent systems that are much more powerful, economical and versatile., capable of working fluidly with text, images, and large volumes of data thanks to technical innovations such as the Mixture-of-Experts architecture and an extremely wide context window.
What is Llama 4 and why is it causing such a stir?
Llama 4 is the fourth iteration of Meta's language models, designed from the ground up to Offer native multimodal capabilities, superior computational efficiency, and more open access to developers and businesses. This means that models now not only understand and generate text, but can also interpret images and integrate them into their responses without the need for independent architectures.
One of its hallmarks is the use of Mixture-of-Experts (MoE) architecture, which allows processing to be distributed across multiple specialized experts, activating only those needed for each task. In this way, computational cost is reduced and performance is improved without having to resort to gigantic dense models. For more information on Meta's new developments, you can check out how Meta has released Llama 4.
Another great milestone in these models is the context window of up to 10 million tokens, something first in the industry, which allows them to handle massive inputs such as entire code repositories or multiple large documents in a single request.
Llama 4 Scout: the compact, fast, and multimodal model
Scout is the lightest model in the family, but no less powerful.. With 17.000 billion active parameters and 16 experts, has been designed to operate in more modest teams, as a single GPU Nvidia H100, making it ideal for enterprise applications or developers without large infrastructures. This highlights the flexibility that the Llama 4 models offer for different platforms, even integrating into WhatsApp and other applications.
Thanks to its optimized architecture and the use of INT4 quantization, Scout achieves a very high inference speed without sacrificing quality. In addition, its context window 10 billion tokens makes it the ideal model for processing and summarizing large amounts of text, such as reports, databases documentaries or complex user activity.
In terms of benchmarking, it has managed to surpass rivals such as Gemini 2.0 Flash-Lite, Mistral 3.1 and Gemma 3 in tasks that combine reasoning, speed and efficient use of resources, despite having fewer active parameters than these models.
Scout is also able to align images with text thanks to MetaCLIP, which allows it to visually interpret prompts and offer connected responses with graphical content, as demonstrated on Ray-Ban smart glasses with Meta AI integration. For more details on these integrations, check out our coverage on How to use Meta AI on Instagram.
Llama 4 Maverick: The versatile expert for complex tasks
The Llama 4 Maverick is the mid-range model within the family and one of the most impressive in terms of performance. It also features 17.000 billion active parameters, but unlike Scout uses up to 128 experts and a total of 400.000 billion parameters. This structure allows you specialize in programming, logical reasoning and complex tasks without penalizing response times.
Meta has placed special emphasis on making it competitive in benchmarks such as coding, math, creative writing, and difficult assignmentsIn ChatBot Arena evaluations, Maverick has placed at the top, tying with higher-end models like the experimental Gemini 2.5 Pro, and beating GPT-4o and Google Gemini 2.0 Flash in several key categories. The competition between these models highlights the importance of technological innovations such as those discussed in the article on Meta facial recognition in Europe.
Another of its outstanding advantages is that, despite competing in quality with models such as DeepSeek 3.1 its computational cost is much lowerThis makes it a very attractive option for companies looking for high-performance AI without wasting resources.
His training has been fine-tuned through Light supervision, online reinforcement learning, and direct preference optimization, achieving an excellent balance between speed, precision and adaptation to the user's intention.
Llama 4 Behemoth: The Titan of Artificial Intelligence
Behemoth is the giant of the new generation. It is not yet publicly available, as it is in training and testing phase, but its specifications already place it as one of the most powerful models on the planetIts arrival marks a milestone in the evolution of AI, which you can follow in our news about Technological advances and demonstrations by Meta.
We talk about 288.000 billion active parameters with 16 experts and nearly 2 trillion total parameters. A real beast that Meta has used as master or "teaching" model to train Scout and Maverick more efficiently through co-distillation processes.
In internal testing, Behemoth has managed to outperform GPT-4.5, Claude Sonnet 3.7 and Gemini 2.0 Pro in benchmarks focused on mathematics, multilingualism and visual interpretation such as GPQA Diamond or MATH-500.
Due to its size, Meta has had to redesign part of its infrastructure, using techniques such as asynchronous reinforcement networks and a new method called GOAT for detecting vulnerabilities during security testing. It has also become an example of how to create specialized models starting from a larger one, following the “distillation” strategy used in other AIs such as DeepSeek.
Commitment to openness, security and responsible use
One of the pillars of Llama 4 is Meta's approach to a More open but also responsible AIAlthough some criticize that it is not completely open source due to certain restrictive licenses, it is true that it provides free weights and sufficient documentation so that developers and researchers can work with these models. The debate about openness in AI resonates with other projects, such as the Meta and verification of professional data.
In addition, Meta has provided Llama 4 with tools to prevent improper or problematic uses, such as Prompt Guard and Llama Guard, systems that filter out inappropriate content or misinformation. The ideological bias of the models has also been significantly reduced, according to internal metrics, allowing more neutral and balanced responses to controversial social issues.
On the other hand, the multimodal aspect has been managed with early integration (early fusion), allowing text and images to share the same architecture without the need for separate modules. This improves consistency and facilitates joint training with mixed datasets.
Access, availability and what's next
Both Scout and Maverick are already available for download from llama.com and Hugging Face. They can also be used natively on platforms such as WhatsApp, Messenger, Instagram Direct and the Meta AI site. For more information about its integration into applications, you can review the article on Meta AI and its relationship with WhatsApp.
In addition, they have been integrated into cloud environments such as Azure, Google Cloud, Cloudflare Workers and DatabricksThis availability makes them a very flexible option for both developers and businesses.
Meta has announced the celebration of the first LlamaCon event On April 29, where new features such as the specialized version are expected Llama 4 Reasoning and a dedicated app for its AI assistants, with potential agent functions such as booking or video production.
This new generation of Llama models not only redefines what open AI can do. It also demonstrates that it is possible to achieve a Powerful, scalable, and accessible AI without sacrificing security and efficiencyWhile Scout and Maverick are already setting a new standard in performance and versatility, Behemoth is shaping up to be the future engine of even more sophisticated and specialized artificial intelligence.
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