Meta has released its latest open-source artificial intelligence model, Llama 4, which includes two main versions: Scout and Maverick. Both models utilize an innovative Mixture of Experts (MoE) architecture, enabling efficient processing of multiple data types, including text, images, videos, and audio.
Key Features:
Llama 4 Scout
- Parameters: 1.7 billion active parameters, with a total of 10.9 billion parameters.
- Hardware Requirements: Can run on a single NVIDIA H100 GPU.
- Capabilities: Supports multimodal input, processing text and up to five images, and features an industry-leading 10 million token context window, making it ideal for tasks such as document summarization and code reasoning.
Llama 4 Maverick
- Parameters: Also has 1.7 billion active parameters, but with a total of 40 billion parameters, supported by 128 expert models.
- Hardware Requirements: Requires more powerful hardware, such as NVIDIA H100 DGX systems.
- Performance: Outperforms OpenAI’s GPT-4o and Google’s Gemini 2.0 Flash in multiple benchmark tests, making it well-suited for creative writing, translation, and long-text summarization.
Llama 4 Behemoth (In Training)
- Parameters: Still under development, expected to have 288 billion active parameters and nearly 2 trillion total parameters.
- Purpose: Designed to be Meta’s most powerful AI model to date, acting as a “teacher” model for training other models, and excelling in STEM-related benchmark tests.
Application Scenarios
- Customer Service: Llama 4 models can act as intelligent assistants, handling customer queries and providing support, thereby enhancing customer experience.
- Education & Tutoring: These models can be used in education, offering personalized learning support and tutoring, helping students solve problems and understand complex concepts.
- Creative Writing: Llama 4 excels in creative writing, generating stories, articles, and other types of text content.
- Professional Use Cases: In legal, financial, and research fields, Llama 4 can assist in data analysis, report generation, and decision-making support.
- Multimodal Applications: With support for text, images, and videos, Llama 4 is ideal for image recognition, visual question answering, and document processing.
- Long-Text Processing: The model’s ability to handle long-context conversations and text makes it well-suited for summarizing and analyzing lengthy articles.
Meta's Llama 4 series is open-source, but its license comes with specific requirements. According to the latest information, Llama 4 Scout and Llama 4 Maverick are officially labeled as "open-source software" and are available for download on Meta’s official website and Hugging Face.