Llama: a plain-English guide

What Llama is and who makes it

Llama is a family of large language models made by Meta, the company behind Facebook, Instagram and WhatsApp. What made Llama special is that Meta published the model weights: anyone who accepts the license can download Llama, run it on their own hardware, fine-tune it and build products with it. Llama quickly became one of the most widely used model families for self-hosting, and many other open models and tools were built on top of it.

Llama is not a chat app in itself. It is a set of models that developers, companies and hobbyists run inside their own apps, on their own servers or through cloud providers.

The Llama model family

Llama has gone through several generations, each available in more than one size:

• Llama 2. The generation that brought open-weight models with commercial use into the mainstream, including chat-tuned versions.
• Llama 3. A big step up, released in several updates (3.1, 3.2 and 3.3). It ranged from small models that run on phones and laptops to a very large model, and added versions that understand images.
• Llama 4. The latest Llama-branded generation, with two released models, Scout and Maverick. Both are natively multimodal and use a mixture-of-experts design, where only part of the model is active for each word, to run more efficiently.

As of October 2026, Meta has not released a newer Llama generation. Its newer AI work appears under a different name, Muse. Muse Spark is a closed model that now powers Meta's own assistant, Meta AI, and in October 2026 Meta released Muse Spark Open, a large open-weight model under a separate Muse license. Existing Llama models remain available for download.

What Llama is good at

• Running on your own hardware. Smaller Llama models run on a single good graphics card or even a laptop, so you can use AI without sending data to anyone.
• Fine-tuning. You can train Llama further on your own documents or examples to make it better at a narrow job, such as support replies in your company's style.
• A huge ecosystem. Popular tools such as llama.cpp, Ollama and vLLM support Llama, and thousands of community fine-tunes exist on Hugging Face.
• Predictable costs. When you host the model, you pay for hardware or cloud time rather than per message.
• Learning and research. Students and researchers use Llama to study how language models work, because they can inspect and modify it.
• Offline and private setups. Llama can run in places with no internet connection or strict data rules.

Limits to keep in mind

Llama is no longer the newest open-weight option. Newer open models from other labs and from Meta's own Muse line are often stronger, so test a few before you commit. Like any model, Llama can produce wrong or made-up answers; check important facts, as explained in our guide on fact-checking AI answers.

Self-hosting also means more responsibility. Larger Llama models need serious hardware, you have to set up updates and monitoring yourself, and safety filters are your job: Meta publishes safety tools, but a raw model will not protect your users by itself. There is also no official Meta chat app dedicated to Llama, because Meta has moved its own assistant, Meta AI, to its newer Muse models.

How to use Llama officially

You can download Llama models from Meta's Llama website (llama.com) or from Meta's page on Hugging Face after accepting the license. Many cloud platforms also offer hosted Llama models, so you can call them through an API without running servers yourself. To try Llama on your own computer, a desktop tool that supports local models is the easiest start. The official link in the facts section of this page goes to Meta's Llama site.

Check the license before you build. Llama uses the Llama Community License, not a standard open-source license. It allows free commercial use for most companies, but it includes an acceptable use policy, attribution and naming rules for derivatives, and a requirement for companies with more than 700 million monthly users to get separate permission from Meta. For Llama 4, the rights to the multimodal models are not granted to individuals or companies based in the EU, although EU end users of products built with them are not affected.

Privacy notes

With Llama, privacy depends on who runs the model. If you run it on your own computer or servers, your prompts stay with you; nothing is sent to Meta. If you use a cloud provider or a third-party app that runs Llama, that provider's privacy policy applies, so read it before sharing sensitive information. Meta AI is a separate product with its own privacy policy. Our AI privacy and safety guide has tips that apply to any setup.

How Llama compares

Among open-weight families, Qwen offers a very wide range of recent models, many under the permissive Apache 2.0 license; DeepSeek publishes very large, strong models under MIT; and Mistral is a European option with both open and commercial models. Closed assistants such as ChatGPT, Claude and Gemini are easier to start with and usually stronger, but you cannot host or modify them. Developers can find practical tips in our AI for coding guide.

FAQ

Is Llama free?

The weights are free to download and use under the Llama Community License. Running the models still costs money for hardware, electricity or cloud time.

Is Llama open source?

Llama is open-weight, but its license has conditions that standard open-source licenses do not, so many people avoid calling it fully open source.

Does Meta AI use Llama?

Meta has moved its assistant, Meta AI, to its newer Muse models, which replaced Llama there. Llama remains available as a separate open-weight family.

Can I run Llama on a laptop?

Smaller Llama models can run on a modern laptop, especially in compressed form. The largest models need powerful servers.

Is ChatG connected to Meta or Llama?

No. ChatG is an independent AI chat website and is not affiliated with Meta. This page is an informational guide. You can try ChatG free in your browser.