Llama (Meta)

Basic Information

• Company/Brand: Meta (formerly Facebook)
• Country/Region: United States
• Official Website: https://www.llama.com / https://ai.meta.com/llama
• Type: Open-source Large Language Model (LLM)
• Launch Date: Llama 1 was released in February 2023

Product Description

Llama is a series of large language models developed and open-sourced by Meta, currently the most popular open-source LLM globally. The Llama 4 series, released in 2026, adopts a Mixture of Experts (MoE) architecture and achieves native multimodal capabilities for the first time. It includes three versions: Llama 4 Scout, Llama 4 Maverick, and Llama 4 Behemoth, competing in performance with top-tier closed-source models.

Core Features/Characteristics

• Llama 4 Scout: 17 billion active parameters, 16 experts, can run on a single H100 GPU (Int4 quantization)
• Llama 4 Maverick: 17 billion active parameters, 128 experts, suitable for a single H100 host
• Llama 4 Behemoth: 288 billion active parameters, 16 experts, surpasses GPT-4.5 and Claude Sonnet 3.7
• Native Multimodality: Uses early fusion technology to seamlessly integrate text and visual tokens
• Strong Multilingual Support: Pre-trained on 200 languages, with over 1 billion tokens for 100+ languages
• MoE Architecture: Mixture of Experts architecture improves inference efficiency and reduces computational costs
• Open-source and Customizable: Full model weights are open, supporting community fine-tuning and customization
• Local Deployment: Can run on consumer-grade hardware using tools like Ollama and llama.cpp

Business Model

• Fully Open-source: Model weights are released for free under the Llama license
• Community-driven: Distributed through platforms like Hugging Face
• Cloud Platform Integration: Major cloud service providers offer Llama hosting services
• Strategic Value for Meta: Open-source strategy helps Meta build an AI ecosystem, benefiting its advertising and social businesses

Target Users

• Open-source community and individual developers
• Enterprises requiring local deployment
• AI researchers and academic institutions
• Users in privacy-sensitive scenarios
• Teams looking to customize and fine-tune models

Competitive Advantages

• The most successful open-source LLM with the richest community ecosystem
• Completely free to use, with no API fees
• Can be run locally, ensuring data privacy
• MoE architecture provides efficient inference
• Multilingual support for 200 languages
• Extensive ecosystem of fine-tuned models and derivatives
• Meta's continuous investment ensures model quality

Market Performance

• The most downloaded open-source LLM globally
• One of the most popular model families on Hugging Face
• Numerous enterprises and developers build products based on Llama
• Llama 4 Behemoth surpasses multiple closed-source models in STEM benchmarks
• Drives the development of the entire open-source AI ecosystem

Relationship with the OpenClaw Ecosystem

Llama is the most important open-source model choice in the OpenClaw ecosystem. Users can run Llama models locally using tools like Ollama and llama.cpp, then integrate them into the OpenClaw platform to achieve fully localized, zero-cost AI agents. Llama 4 Scout is particularly suitable for individual users—running on a single consumer-grade GPU, providing OpenClaw with powerful local inference capabilities without relying on cloud APIs.