Llama is a family of generative AI models developed by Meta. The first release arrived in February 2023 as a foundational language model for researchers, and the family later expanded into text, coding, vision, and multimodal models.

What is Llama?

The name originally stood for Large Language Model Meta AI. Llama is not one assistant or one fixed model. It is a family whose capabilities, model sizes, context windows, hardware needs, and license terms differ by release.

How does Llama work?

Like other large language models, Llama learns statistical patterns from training data and predicts the next token. Instruction-tuned versions are optimized to follow prompts, while some newer releases can understand both text and images and can support tool use.

What are the main generations?

Meta introduced LLaMA in February 2023, followed by Llama 2 in July 2023, Llama 3 in April 2024, and later 3.1, 3.2, 3.3, and Llama 4 Scout and Maverick. Important releases should have separate pages because their specifications are not interchangeable.

Is Llama open source?

Meta describes Llama as open and broadly available, but each release is distributed under a Llama Community License rather than one standard open-source software license. Developers should review the license attached to the exact model they plan to use.

Strengths

  • Weights for many releases can be downloaded and deployed on infrastructure selected by the developer.
  • The family includes multiple sizes and text, coding, vision, and edge-oriented variants.
  • A broad partner ecosystem supports hosting, fine-tuning, and application development.

Limitations and risks

Meta documents risks including bias, toxicity, and misinformation and publishes model cards and safety tools. Performance, hardware requirements, licensing, and safeguards vary significantly across releases, so claims about one Llama model should not be generalized to the entire family.

In short

Llama is Meta’s model family, not a single model. Its main appeal is deployment and customization flexibility, but choosing it requires attention to the specific release, license, capabilities, and operating requirements.