Llama 4 Free

Llama 4 is Meta’s open-weight family of natively multimodal models, released in April 2025. It ships in two main variants: Scout with a 10 million token context window, and Maverick with 17 billion active parameters per token. Weights are downloadable, and the licence permits most commercial use.

What is Llama 4?

Llama 4 is the fourth generation of Meta’s Llama models. The headline change is architecture: both variants are mixture-of-experts, and both take text and images as input from the ground up rather than bolting on a vision encoder later.

Scout is the long-context model, built for stuffing in entire books or code repositories. Maverick is the generalist, with 400 billion total parameters and 17 billion active at any one time.

What are Llama 4’s key specs?

• Scout. 109 billion total parameters, 17 billion active, 10M-token context, single H100 can serve it.
• Maverick. 400 billion total parameters, 128 experts, fits on a single host with 8 H100s.
• Native multimodality. Early fusion means images are tokens, not an add-on.
• Multilingual. Officially tuned for 12 languages including Arabic, Hindi and Spanish.
• Open weights. Downloadable from Meta and Hugging Face under the Llama 4 Community Licence.
• Hosted options. Available through Meta AI, Groq, Together and most major clouds.

Product Highlights

• The 10M context is the real story. Scout can take roughly 7,500 pages of text in one prompt, no retrieval layer needed.
• No charge for the weights. Self-host at your own GPU cost; there is no per-token fee from Meta.
• Broad deployment. Runs on vLLM, Ollama, llama.cpp and hosted APIs.
• Vision at launch. Image questions work out of the box, unlike Llama 3.

Should you use Llama 4?

Llama 4 makes sense when you need open weights, on-prem deployment, or a context window nobody else offers. Scout on a single H100 is a genuinely useful option for document-heavy pipelines.

Be realistic about quality. Independent evaluations put Llama 4 Maverick below Gemini 2.5 Pro and GPT-4o on many reasoning and coding tasks, and Meta’s own launch benchmark claims were disputed by some researchers. The licence also adds conditions for companies with over 700 million monthly users, so it is not fully unrestricted.

Use Cases

• Processing entire codebases or book-length documents in one call
• On-premise assistants for regulated industries
• Multilingual customer support across 12 languages
• Image-plus-text document understanding
• Fine-tuning on a private domain dataset

Quick Summary

• Llama 4 is Meta’s open-weight, natively multimodal model family from April 2025.
• Scout offers a 10M-token context window and runs on a single H100.
• Maverick has 400B total and 17B active parameters.
• Weights are free to download but the licence is not fully unrestricted.
• Good for long-context and on-prem work; behind frontier models on hard reasoning.