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Meta’s Llama 4 is here with Scout and Maverick AI models

Meta’s Llama 4 Scout crushes it on one GPU, Maverick rivals GPT-4o, and Behemoth’s coming.

By
Shubham Sawarkar
Shubham Sawarkar's avatar
ByShubham Sawarkar
Editor-in-Chief
I’m a tech enthusiast who loves exploring gadgets, trends, and innovations. With certifications in CISCO Routing & Switching and Windows Server Administration, I bring a sharp...
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Apr 6, 2025, 1:18 PM EDT
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Meta Llama 4 blog header image
Image: Meta
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It’s April 2025, and Meta—the tech giant behind your endless Instagram scrolls and WhatsApp chats—has just unleashed two shiny new AI models under the Llama 4 banner. These bad boys are already powering the Meta AI assistant across their platforms, from the web to your favorite messaging apps. And if you’re a tech nerd who loves tinkering, you can snag them for yourself on Meta’s site or Hugging Face.

First up, we’ve got Llama 4 Scout. Think of it as the scrappy little sibling who punches way above its weight. Meta says this model is so compact it can run on a single NVIDIA H100 GPU—basically the tech equivalent of fitting a whole circus into a clown car. Don’t let its size fool you, though. Scout boasts a jaw-dropping 10-million-token context window (that’s AI-speak for how much it can “remember” at once), and it’s apparently smoking the competition—Google’s Gemma 3, Gemini 2.0 Flash-Lite, and even the open-source darling Mistral 3.1—across a slew of benchmarks. If you’re into AI scorecards, this is the underdog you’d bet on.

Meta Llama 4 Scout instruction-tuned benchmarks
Image: Meta

Then there’s Llama 4 Maverick, the bigger, bolder brother. This one’s playing in the big leagues, going toe-to-toe with heavyweights like OpenAI’s GPT-4o and Google’s Gemini 2.0 Flash. Meta’s tossing around some flex-worthy claims here, saying Maverick matches up to DeepSeek-V3 in coding and reasoning tasks while using “less than half the active parameters.” Translation? It’s efficient, powerful, and probably smug about it. If AI models had personalities, Maverick would be the guy showing off his gym gains.

Meta Llama 4 Maverick instruction-tuned benchmarks
Image: Meta

Oh, and there’s a third model in the works: Llama 4 Behemoth. It’s not out yet—Meta’s still training this beast—but they’re already hyping it up like it’s the second coming of AI. With 288 billion active parameters and a whopping 2 trillion parameters total, Behemoth is poised to take on the likes of GPT-4.5 and Claude Sonnet 3.7, especially in STEM-heavy tasks. Mark Zuckerberg himself chimed in, calling it “the highest performing base model in the world.” Bold words, Zuck. We’ll believe it when we see it at the big reveal.

Meta Llama 4 Behemoth instruction-tuned benchmarks
Image: Meta

So, what’s the secret sauce behind Llama 4? Meta’s gone all-in on a “mixture of experts” (MoE) approach. Imagine an AI model as a Swiss Army knife: instead of flipping out every tool for every job, MoE only uses the ones it needs. It’s like calling in a specialist instead of a whole crew—saves energy, cuts costs, and still gets the job done. Smart, right? They’re planning to spill more tea about this—and their future AI dreams—at LlamaCon on April 29th. Mark your calendars if you’re into that sort of thing.

Open-source? well, sort of

Meta is slapping the “open-source” label on Llama 4, just like they did with past models. But hold up—there’s a catch. The fine print says if you’re a commercial outfit with over 700 million monthly active users, you’ve got to ask Meta nicely before you can play with their toys. That little clause has had folks like the Open Source Initiative crying foul for years. Back in 2023, they argued it’s enough to kick Llama out of the true open-source club. So, it’s more like “open-ish”—free for some, a polite negotiation for others.

If you’re not an AI geek, you might be wondering what this means for you. Well, these models are already juicing up Meta AI, the assistant you’ve probably chatted with on WhatsApp or Instagram. Scout and Maverick could make it faster, smarter, and better at understanding your rants about last night’s Netflix binge. And if Behemoth lives up to the hype, who knows? Maybe it’ll help Meta tackle bigger problems—or at least write you a killer physics essay.

For the broader tech world, this is another salvo in the AI arms race. OpenAI, Google, and now Meta are all duking it out to build the brainiest models, and Llama 4’s efficiency tricks might just give Meta an edge. Plus, with Scout fitting on a single GPU, it’s a win for smaller devs who don’t have a server farm in their basement.

Zoom out a bit, and this is classic Meta: pushing boundaries while stirring the pot. Their AI game’s been heating up since Llama first dropped, and they’re clearly not here to play small. But that “open-source” debate? It’s a reminder that even in the wild west of AI, there’s still plenty of gray area. Are they truly sharing the love, or just flexing control in a friendlier package?

For now, Scout and Maverick are here, Behemoth’s on deck, and the tech world’s buzzing. Whether you’re a coder, a casual user, or just someone who likes a good story, Llama 4’s worth keeping an eye on. Who knows what Meta’s got up its sleeve next? Guess we’ll find out at LlamaCon—or when Behemoth finally stomps onto the scene.


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