Meta’s Llama is a family of open generative AI models designed to empower developers with flexible, accessible tools for building AI applications. Unlike closed models such as OpenAI’s ChatGPT or Google’s Gemini, Llama is released under a permissive license that allows developers to download, use, modify, and deploy the models freely—subject to certain restrictions. This openness has made Llama a cornerstone of the open-source AI movement. The latest version, Llama 4, was released in April 2025 and includes three distinct models: Llama 4 Scout, Llama 4 Maverick, and Llama 4 Behemoth. Each is tailored for different use cases and performance needs. Llama 4 Scout features a massive 10 million-token context window—equivalent to about 80 average novels—making it ideal for processing long documents, complex codebases, or extensive research data. Llama 4 Maverick offers a 1 million-token context window and balances reasoning, speed, and efficiency, making it well-suited for coding, chatbots, and real-time applications. Llama 4 Behemoth, with 16 experts in its mixture-of-experts (MoE) architecture, is designed for advanced research, model distillation, and demanding STEM tasks. All Llama 4 models are natively multimodal, trained on vast amounts of unlabeled text, image, and video data, and support 200 languages. The MoE design improves efficiency by activating only a subset of model parameters per input, reducing computational cost during inference. Llama 4 builds on the success of Llama 3.1 and 3.2, which were widely adopted for instruction tuning and cloud deployment. Developers can extend Llama’s capabilities by integrating third-party tools. For example, the models can be configured to use Brave Search for up-to-date information, Wolfram Alpha for math and science queries, and a Python interpreter for code validation—though these require manual setup. Llama is available through multiple channels. It powers Meta AI across Facebook Messenger, WhatsApp, Instagram, Oculus, and Meta.ai in over 40 countries, with fine-tuned versions used in more than 200 countries and territories. Developers can access Llama 4 Scout and Maverick on Llama.com and platforms like Hugging Face. Over 25 cloud and hardware partners, including AWS, Google Cloud, Microsoft Azure, Nvidia, Databricks, Groq, Dell, and Snowflake, host and optimize Llama for deployment. While Meta doesn’t sell direct access to the models, it earns revenue through revenue-sharing agreements with hosting partners. A notable initiative launched in May 2025 is Llama for Startups, which provides startups with technical support, access to Meta’s Llama team, and potential funding to encourage adoption. To enhance safety, Meta offers a suite of tools. Llama Guard detects harmful content such as hate speech, self-harm, and illegal activity. Prompt Guard defends against jailbreak attempts and malicious inputs. Llama Firewall identifies prompt injection and insecure tool use, while Code Shield helps prevent insecure code generation across seven programming languages. CyberSecEval is a benchmark suite that evaluates model security risks, including potential for automated social engineering or cyberattacks. Despite its strengths, Llama has limitations. Multimodal capabilities are currently limited to English. The models were trained on large datasets, including pirated e-books and social media content from Facebook and Instagram—controversial practices that sparked legal challenges. A federal judge ruled in Meta’s favor, citing fair use, but users risk copyright liability if they reproduce copyrighted content generated by the model. Llama also struggles with code quality. On LiveCodeBench, Llama 4 Maverick scored 40%, significantly below OpenAI’s GPT-5 (85%) and xAI’s Grok 4 Fast (83%). Developers should always review AI-generated code before deployment. Like all generative AI, Llama can produce plausible but false information, especially in legal, medical, or technical contexts. Users should treat its outputs as suggestions, not definitive answers. Llama remains a powerful, flexible, and rapidly evolving platform—driving innovation in open AI while raising important questions about ethics, safety, and intellectual property.