Meta has just raised the bar again with the release of Llama 4, its latest lineup of AI models launched in April 2025. These models bring powerful upgrades that boost performance, efficiency, and versatility like never before. Let’s dive into the top three features that make Llama 4 truly next-level

3. Smarter and Faster with Mixture of Experts (MoE)

One of the biggest upgrades in Llama 4 is the switch to a Mixture of Experts (MoE) architecture — a major leap from the dense models in earlier versions like Llama 3.

How It Works:

• Instead of activating all parameters for every input, MoE activates only a small portion.
  
  
• For instance, Llama 4 Maverick uses just 17 billion out of 400 billion parameters with help from 128 “experts” (mini neural networks) and one shared expert.
  
  
• Even the most compact version, Llama 4 Scout, uses this smart approach with 16 experts and only activates the required parts.
  
  
• The largest model, Llama 4 Behemoth, taps into 288 billion active parameters from a massive pool of nearly 2 trillion.

Why It Matters:

• This results in faster performance, lower computing costs, and reduced latency.
  
  
• Impressively, these models can even run on a single Nvidia H100 GPU, unlike other large AI systems that require multiple GPUs.

2. Built-in Multimodal Understanding: Text + Images Together

Another exciting feature of Llama 4 is its native multimodal capability — meaning it can process both text and images at the same time.

What’s New:

• Text and visual data are fused right from the training phase, creating a more unified and intelligent model.
  
  
• Unlike earlier releases that needed separate vision and text models, Llama 4 handles both in one.
  
  
• It uses an enhanced vision encoder that enables complex visual reasoning and support for multi-image inputs.

What This Enables:

• Better understanding of combined content (e.g., explaining images with context).
  
  
• Great fit for applications in design, education, research, and more.

1. Massive 10 Million Token Context Window

Llama 4 introduces a record-breaking context window — with support for up to 10 million tokens in the Scout model. That’s over five million words of continuous input!

How It Compares:

• Llama 3 originally supported just 8,000 tokens, later upgraded to 128K.
  
  
• Now, Llama 4 Scout offers 10 million tokens, while Maverick supports up to 1 million — both major leaps.
  
  
• For reference, Google’s Gemini supports 2 million tokens, and GPT-4.5 handles 128K — making Llama 4 the new industry leader.

Why It’s a Big Deal:

• Handles long documents, entire codebases, and deep analytical tasks with ease.
  
  
• Supports extended conversations without losing context — a major win for chatbot and assistant use cases.

Final Thoughts: Llama 4 Is Setting a New Standard

With its efficient MoE design, built-in multimodal support, and massive context handling, Meta’s Llama 4 models are redefining what open-weight AI can do. Whether you're building apps that rely on text, images, or large-scale reasoning, Llama 4 is ready to take on the challenge.

** If you're exploring high-performance AI tools for your project, keep an eye on Llama 4 — it’s shaping up to be a serious rival to even the biggest names in AI.