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Meta's Llama 4 family arrived in April 2025 as one of the most significant open-weight AI releases ever — and in 2026, it remains the backbone of hundreds of apps, research projects, and free AI tools worldwide. Whether you're a developer building a product or just someone looking to use a powerful AI without paying for ChatGPT Plus, here's everything you need to know.Llama 4 is Meta's fourth generation of open-weight large language models, released under a custom license that allows commercial use for most businesses. Unlike closed models from OpenAI or Anthropic, Llama 4 weights can be downloaded and run locally — or accessed for free through several platforms.
The Llama 4 family has three main models, each built for a different use case:
::keyfacts
- **Llama 4 Scout** — 17B active parameters (109B total), 10M token context window, multimodal
- **Llama 4 Maverick** — 17B active parameters (400B total), best multimodal reasoning
- **Llama 4 Behemoth** — 288B active (2T total), Meta's frontier/teacher model
::end
All three use a **Mixture of Experts (MoE)** architecture, meaning only a fraction of parameters activate per token — delivering better performance per compute dollar than dense models.
## Llama 4 Scout: The Speed King
Scout is the model most people will actually use. With 17 billion active parameters and a 10-million-token context window, it can process entire codebases, long research papers, or hours of conversation history in a single call.
**Key Scout specs:**
- 109 billion total parameters, 17B active per forward pass
- 10M token context window (the longest of any freely available model)
- Natively multimodal: text, images, and documents
- Runs on a single H100 GPU at full precision
For developers, Scout is a game-changer for RAG (retrieval-augmented generation) applications — you can stuff enormous amounts of context directly into the prompt instead of building complex retrieval pipelines.
## Llama 4 Maverick: The Multimodal Powerhouse
For full coverage, visit https://www.linos.ai/technology/meta-llama-4-release-features-benchmarks-2026/
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