What is Llama? — AI Glossary

What it is: Llama is the family of open-weight large language models from Meta AI. It’s the most influential open-source model family in AI — by releasing Llama free for most uses, Meta reshaped how the open-source AI ecosystem developed.
Who it is for: Developers, researchers, and companies wanting capable language models without paying per-token API fees to OpenAI or Anthropic.
Best if: You need to run AI on your own servers (for privacy, cost, or customization) and want a model with strong community support and broad ecosystem.
Skip if: You’re a casual user with no technical workflow — you’ll interact with Llama through other products without ever calling it “Llama.” Want one practical AI workflow every morning? Subscribe to our free daily newsletter.

What is Llama?

Llama (Large Language Model Meta AI) is the family of large language models released by Meta AI, starting with Llama 1 in February 2023. Each generation — Llama 1, Llama 2, Llama 3, Llama 3.1, Llama 4, Llama 5 — has been released as open-weight, meaning the model files can be downloaded and run by anyone (with some commercial-use restrictions in the license).

Llama models come in several sizes (typically 1B, 3B, 8B, 70B, and 400B+ parameter variants). Smaller versions run on a laptop; the largest ones require multiple GPUs. Mid-size versions (~70B parameters) are the sweet spot — they roughly match GPT-4-class quality and run on commercially available hardware.

Why does Llama matter?

Llama’s open-weight release reshaped the AI industry. Before Llama, capable AI was effectively only available via paid APIs from OpenAI, Anthropic, and Google. After Llama, anyone could download a model that performed competitively, fine-tune it on their own data, and run it on their own infrastructure — without sending sensitive data to a third party.

That single decision created a thriving open-source AI ecosystem: thousands of fine-tuned variants on Hugging Face, libraries like vLLM and llama.cpp for fast local inference, hardware optimization for consumer Macs and PCs, and a generation of startups building on open weights rather than per-token APIs. Competitors like Mistral, DeepSeek, and Google’s Gemma followed Meta’s playbook.

How do you use Llama?

Three main paths:

• Through Meta’s products. The Meta AI assistant inside WhatsApp, Instagram, Facebook Messenger, and Ray-Ban Meta smart glasses is powered by Llama. If you’ve chatted with Meta AI, you’ve used Llama.
• Via third-party hosts. Many cloud providers offer Llama through their own APIs (Groq, Together AI, Fireworks, Anyscale, AWS Bedrock). You pay per-token like OpenAI but the underlying model is open and swappable.
• Self-hosted. Download from Hugging Face and run with tools like Ollama (consumer-friendly), llama.cpp (efficient CPU/GPU), or vLLM (production serving).

Related terms

• Meta AI
• Open Weights
• Hugging Face
• Mistral
• Large Language Model

Learn more on Beginners in AI

• Ollama — Run Llama Locally
• AI Glossary

Sources and further reading

• Llama — official Meta page
• Llama on Hugging Face
• Llama — Grokipedia

Last reviewed: May 2026. AI terminology evolves quickly — verify specifics on the official source pages above.

You may also like

• Ollama — Run Llama Locally
• AI Glossary
• Meta AI
• Open Weights
• Hugging Face
• Mistral