Llama
Last updated June 14, 2026
What is Llama in simple terms?
In simple terms, Llama is a family of AI language models made by Meta that you can download and run yourself, instead of only renting access through someone else's website — think of it as the engine.
What is Llama?
Llama is a family of large language models built by Meta, distinguished from most rivals by being released as open-weight models that developers, researchers, and companies can download and run on their own systems, rather than only using through one company's app.
Llama is a family of large language models created by Meta, the company behind Facebook, Instagram, and WhatsApp. The name is shorthand for "Large Language Model Meta AI." Like other large language models, each Llama is trained on enormous amounts of text so it can understand language and generate fluent replies. The thing that sets Llama apart from many well-known rivals is how it's distributed. Where assistants like ChatGPT or Gemini are used mainly through one company's app or service, Meta releases Llama as *open-weight* models — it publishes the trained model itself so that developers, researchers, and businesses can download it, run it on their own computers or servers, and build their own products on top of it.
This open-weight approach is the heart of why Llama matters, and it's worth being precise about. "Open weight" means the finished model is made freely available to download and use; it does *not* automatically mean fully open-source software in the strict sense. Meta releases Llama under its own license with conditions attached, and some organizations argue that those conditions stop it from counting as genuinely open-source. The practical upshot for most people, though, is real: because you can run Llama yourself, you can keep your data on your own systems, adapt the model to a specific task by fine-tuning it, and avoid depending on a single provider — trade-offs that a company handling sensitive data, or a developer who wants full control, often values highly.
Because of this, Llama tends to show up less as a consumer chat app you'd open by name and more as the quiet engine inside other people's tools. A great many AI features, internal company assistants, and research projects are built on a Llama model under the hood. Like every large language model, it can still be confidently wrong (a hallucination) and shouldn't be trusted blindly — running a model yourself gives you control, not correctness. Llama's significance is less about being the single "best" model on any given day and more about putting a capable, freely downloadable model into the hands of anyone who wants to build with it.
Real-world example of Llama
Picture a small regional hospital that wants an AI tool to help staff search years of internal policy documents in plain language — but is firmly told by its lawyers that patient-adjacent information must never leave the building's own servers. Sending those documents off to an outside AI service is a non-starter. So its small IT team downloads a Llama model and runs it entirely on the hospital's own hardware, fine-tuned on that pile of internal policies, with nothing ever sent to an outside company. Staff get a useful question-and-answer assistant; the sensitive material stays in-house the whole time. That's the kind of job open-weight models are chosen for — not because Llama is necessarily the cleverest option available, but because being able to run it yourself, behind your own walls, is the whole point.
Related terms
Frequently asked questions about Llama
What is the difference between Llama and ChatGPT?
The biggest difference is how you get to use them. ChatGPT is a product you access through OpenAI's app or service — the underlying model stays on OpenAI's systems and you rent access to it. Llama is a family of models Meta releases as open-weight, meaning you can download the model itself and run it on your own computers or servers. So ChatGPT is something most people use directly as an assistant, while Llama is more often the engine other developers build their own tools around. The right choice depends on whether you want a ready-made assistant or control over running and adapting the model yourself.
How does Llama work?
Llama works like other large language models: it was trained on vast amounts of text to learn the patterns of language, so it can predict and generate fluent, relevant text in response to what you give it. The distinctive part isn't the inner workings but the access — Meta publishes the trained model so that others can download it, run it on their own hardware, and refine it for specific tasks through fine-tuning. When someone builds a product on Llama, their software feeds your input to the model and passes its generated reply back to you, often without you ever seeing the word "Llama" at all.
What is Llama used for?
Because it can be downloaded and run privately, Llama is widely used as the engine inside other software: company chat assistants, customer-support tools, document search, coding helpers, and a great deal of research. Organizations reach for it when they want to keep data on their own systems, adapt a model to a niche task, or avoid relying on a single outside provider. As with any large language model, it's suited to drafting, summarizing, answering, and assisting — with a human checking anything that matters, since it can still be confidently wrong.