Meta launches Llama 4 series: Multimodal AI with record-breaking capabilities
LLaMA 4 Scout, equipped with 17 billion active parameters and 16 experts, runs efficiently on a single NVIDIA H100 GPU and introduces an industry-first 10 million token context window. It surpasses competitors like Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 in performance.
On the other hand, LLaMA 4 Maverick also features 17 billion active parameters but scales up with 128 experts and a total of 400 billion parameters. It outperforms GPT-4o and Gemini 2.0 Flash in benchmark tests, all while remaining cost-effective.
Introduction to Llama 4 Series
The Llama 4 series has been introduced as an innovative family of open-weight, natively multimodal AI forms. Meta offers a high-performance personalized experience across applications. These include Llama 4 Scout and Llama 4 Maverick. Both hybrids work through a mixture-of-experts or MoE architecture aimed at providing efficient training, reasoning, and multimodal capability.
Llama 4 Scout can effectively run without a single NVIDIA H100 GPU when its active parameters are 17 billion with 16 experts. It has an industry-leading 10 million-token context window and outperforms competitors like Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1.
Meanwhile, Llama 4 Maverick also possesses 17 billion active parameters but boasts 128 experts and a total of 400 billion parameters. This model stands out in comparison to strict standards set by GPT-4o and Gemini 2.0 Flash.
Advancements in Llama 4 Models
Both Llama 4 Scout and Maverick were distilled from Meta’s largest AI model, Llama 4 Behemoth, which has 288 billion active parameters. Behemoth has surpassed GPT-4.5, Claude Sonnet 3.7, and Gemini 2.0 Pro in STEM benchmarks.
Advances in the Llama 4 models include better vision encoders, extended contexts, and enhanced image-text understanding. Post training, innovations such as adaptive reinforcement learning and improved supervision tactics contribute to enhanced multimodal and reasoning capabilities.
Meta's Safety Tools and Accessibility
Meta has introduced safety tools like Llama Guard, Prompt Guard, and CyberSecEval to ensure better content moderation and quality assurance in cybersecurity, along with updated bias mitigation strategies.
Developers can access Llama 4 Scout and Maverick from llama.com, Hugging Face, or through Meta AI in apps like WhatsApp and Messenger. These advancements facilitate open AI progress and encourage the development of intelligent, scalable, efficient, and responsible applications.
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