What Is Llama? Meta’s Open Weights and Licensing
Llama is Meta’s model family, distinct from a chat app or llama.cpp. Using Scout and earlier releases, this article explains mixture-of-experts parameters, language support and specific community license limits.
Meet this model
Llama is Meta’s AI model family with downloadable weights for building inference services and applications. It is distinct from the Meta AI chat product and from llama.cpp, a tool for running models. The family includes multiple generations and sizes. Check vision and language support in the specific model card. Open weights do not imply a standard MIT or Apache license: Llama 4 uses its own community license.
The model name differs from the local runtime
Meta’s repository lists small Llama 3.2 text models separately from vision models, while Llama 4 uses a different mixture-of-experts architecture. The Llama brand alone does not establish image-analysis support. A chat app handles interaction and a runtime loads weights; the model card defines a release’s input and output types.
To generate maintenance descriptions from equipment photos locally, choose an image-input model and its matching image processor. A text-only model does not understand an image merely because a file path appears in the message. Confusing a runtime’s ability to open a file with a model’s ability to interpret it makes troubleshooting unreliable.
Scout illustrates parameter and language limits
The official Llama 4 Scout card lists 17 billion active and 109 billion total parameters, with text and image input and text or code output. The 17B in its name is an active count, not the full weights of a conventional 17-billion-parameter dense model. The official repository provides quantized execution instructions, with hardware requirements tied to precision and inference configuration.
Chinese is absent from the 12 supported languages named in that model card. The model may respond in additional languages, but a Chinese response does not establish an official promise of equal Chinese-language quality. For Chinese knowledge-base or support tasks, evaluate terminology and negated conditions separately instead of transferring conclusions from English evaluations.
Downloadable weights still carry license conditions
The Llama 4 Community License grants specified usage and distribution rights and includes attribution and acceptable-use requirements. Products meeting the agreement’s very large monthly-active-user condition must request separate permission from Meta. A public repository or downloadable weights therefore do not establish an unrestricted standard open-source license.
As of October 20, 2026, the official model cards and download instructions for these releases remain available. Scout is used here as a verifiable example, without claiming that it is the newest or strongest Llama model. This article does not test local deployment. Check the target version’s license, resource requirements and output quality on real inputs before adopting it.
Checked sources
These sources support the concepts and methods described here. Examples and test scope are labeled separately; check the version of the tools you use.