Meta released a new generation of artificial intelligence models under its Llama family, dubbed Llama 4. The new collection includes three distinct models, Scout, Maverick, and Behemoth, each designed with specialized capabilities in multimodal reasoning, large-scale text processing, and STEM-intensive tasks.
Meta disclosed that all three models were trained on extensive datasets comprising unlabeled text, images, and video to give them broad visual and linguistic understanding. While Scout and Maverick are immediately available through Meta’s platforms and partners like Hugging Face, Behemoth remains under training, slated for release later this year.
So, what’s the big deal? Let’s break it down, step by step, and see why this could be a game-changer, or at least a very loud splash in the tech pond.
Imagine AI that can read, see, and think (well, sort of) all at once. That’s the promise of Llama 4.
Meta says these models were trained on massive piles of text, images, and videos, stuff that wasn’t even labeled, meaning the AI had to figure things out on its own, kind of like a kid learning from a messy toy box.
This gives them what Meta calls “broad visual understanding,” which is a fancy way of saying they can handle more than just words, they can “see” and process pictures and videos too.
There are three stars in this lineup:
Scout: Think of it as the nimble little helper. It’s got 17 billion active parameters (we’ll get to what that means in a sec) and can chew through huge documents—up to 10 million tokens, or bits of text. That’s like reading an entire library in one go! It’s perfect for summarizing reports or digging into big code projects, and it runs on a single Nvidia H100 GPU, which is a powerful but fairly common piece of hardware.
Maverick: This one’s the chatty all-rounder, with 17 billion active parameters out of a whopping 400 billion total. It’s built for things like writing stories or helping with coding, and Meta claims it beats out heavyweights like OpenAI’s GPT-4o and Google’s Gemini 2.0 in some tests. It needs beefier gear, though, an Nvidia H100 DGX system.
Behemoth: Still in the oven, this monster has 288 billion active parameters and nearly two trillion total. Meta says it’s already outpacing some top models in math and science tasks, but it’ll need serious hardware to run when it’s ready.
Why the weird names? No clue, Meta’s keeping it playful, I guess. But the real kicker is how these models work. They use something called a “mixture of experts” (MoE) approach.
Picture a team of specialists: instead of one big brain doing everything, the model splits tasks among smaller “experts” that kick in when needed. For Maverick, only 17 billion of its 400 billion parameters are active at once, which saves power and money. Smart, right?
Word on the street, or at least in tech circles, is that Meta got a wake-up call from a Chinese AI lab called DeepSeek. Their models, like R1 and V3, have been stealing the spotlight, matching or even beating Meta’s older Llama models while costing less to run.
Sources say Meta set up “war rooms” to crack DeepSeek’s secrets, especially how they slashed expenses. This competition lit a fire under Meta, and Llama 4 is the result. Timing it for a Saturday? Maybe they couldn’t wait to show off.
Who gets it and who doesn’t?
Scout and Maverick are out now, you can grab them from Llama.com or Hugging Face, a popular AI platform. Behemoth’s still cooking, so no dice there yet. Meta’s also plugged Llama 4 into its AI assistant, Meta AI, which runs on apps like WhatsApp and Instagram in 40 countries.
If you’re in the U.S., you get the fancy multimodal stuff, text and images together, but everyone else has to wait.
If you’re in the European Union, tough luck, Meta’s banned you from using or sharing Llama 4, probably because of the EU’s strict AI and privacy laws. Meta’s grumbled about these rules before, calling them a hassle.
And if you’re a big company with over 700 million monthly users, think Google or TikTok, you need a special license from Meta, which they can approve or deny on a whim. That’s raised some eyebrows among developers who love open-source stuff but hate gatekeepers.
Let’s talk numbers. Parameters are like the brain cells of an AI, the more it has, the smarter it can be. Maverick’s 400 billion total parameters sound huge, but only 17 billion work at once, thanks to that MoE trick.
Scout’s got a 10 million token context window, insane when you consider most models top out at 128,000 or so. That means it can handle War and Peace times ten without breaking a sweat.
Meta’s internal tests say Maverick beats GPT-4o and Gemini 2.0 in coding, reasoning, and image tasks, but it’s not quite up to snuff against the latest from Google (Gemini 2.5 Pro) or Anthropic (Claude 3.7 Sonnet). Behemoth, when it’s done, might take on those big dogs in math and science.
Still, none of these are “reasoning” models like OpenAI’s o1, which double-check their work but take longer to answer. Llama 4’s more of a quick-talker—fast, but not always deep.
Research backs this up. A 2024 study from Stanford showed MoE models can cut energy use by up to 40% compared to traditional setups, which is huge when AI training can cost millions . Stats from Hugging Face say Llama 3 had over 650 million downloads, so Llama 4’s got a big audience waiting.
Meta tweaked Llama 4 to dodge fewer “contentious” questions. Older models would shut down if you asked about hot-button issues like politics, but Llama 4’s more chatty. Meta says it’s “dramatically more balanced” and won’t judge your questions.
A spokesperson told US based media TechCrunch, “You can count on it to provide helpful, factual responses without judgment.” That’s a jab at critics, like Elon Musk and David Sacks, who’ve slammed AI chatbots for being too “woke” or biased toward liberal views.
This comes amid a political firestorm. Musk, who runs xAI, and Sacks, a Trump ally, have called out models like ChatGPT for censoring conservative takes. But here’s the rub: bias in AI isn’t easy to fix. Even xAI’s bots lean one way or another. Meta’s trying to thread the needle, answer more, offend less, but it’s a tightrope walk.
So, what does this all mean? Scout’s low hardware needs might spark a wave of small-scale projects, while Maverick’s chat skills could power new apps.
Behemoth? That’s the wild card, could it rival the big proprietary models?
But those EU restrictions and license rules might slow things down.
If Meta wants Llama 4 to go global, they’ll need to navigate a maze of laws and developer gripes.
Plus, with DeepSeek and others nipping at their heels, the pressure’s on to keep innovating.
As Meta put it in their blog, “This is just the beginning for the Llama 4 collection.” Translation: they’re not done yet.
Open-source fans will cheer, but regulators and rivals won’t make it easy.
Stay tuned, folks, this story’s got legs.
