Meta Llama 4: The Open Source AI That Reinvented the Game
@nascimentoab
Posted 1d ago · 2 min read
Meta Llama 4: The Open Source AI That Reinvented the Game
In April 2025, Meta took a decisive step. The launch of Llama 4 wasn't just an update — it was a break with everything the Llama line had represented until then.
For the first time, Meta adopted the Mixture of Experts (MoE) architecture, the same technique used by the world's most advanced models. The result? Giant model quality with compact model inference costs.
What is the MoE Architecture?
Instead of activating all parameters for each processed token, MoE divides the model into "experts." For each input, only a fraction of them is activated.
Llama 4 Scout has 109 billion total parameters, but activates only 17 billion per token. Maverick reaches 400 billion total parameters with the same 17 billion active. Small model execution cost, huge model capacity.
Three Models, Three Purposes
Llama 4 Scout was designed for extended contexts. Its context window reaches 10 million tokens — the largest ever recorded in an open source model.
Llama 4 Maverick is production-focused. It leads in real software engineering tasks, achieving 85.5% on MMLU.
Llama 4 Behemoth is the largest model in the family — still training at launch time. Positioned as Meta's cutting-edge research model.
Benchmark Performance
MMLU (general knowledge): 85.5% — Maverick
SWE-bench+ (real software engineering): leading performance
Context: 10 million tokens — Scout
License and Availability
Llama 4 uses the Meta Community License. Free for commercial use, with restrictions for companies with over 700 million monthly users.
Available via Hugging Face, Meta AI, AWS Bedrock, Azure, and Google Cloud.
Why This Matters
Llama 4 isn't just a model. It's a platform. Meta opened the model weights, allowing researchers, startups, and companies to build on top of them.
In datacenters and corporate environments, this translates to reduced inference costs with capability equivalent to the most expensive closed proprietary models.
Conclusion
Llama 4 consolidated Meta as the leading open source player in large-scale LLMs. With MoE as its foundation, the line establishes a new standard: efficiency without sacrificing capacity.
Sources: