Meta just released two new AI models: Llama 4 Scout and Llama 4 Maverick. And there’s a third one still training, called Llama 4 Behemoth. Meta says these models can outperform top competitors like OpenAI’s GPT-4o and Google’s Gemini. They’re also available for download now, at least for most people.
Also read: OpenAI New Model, GPT-4.5, Accessible to ChatGPT Plus Users
The Llama 4 Models
| Model Name | Strengths |
| Scout | It is light and fast, and runs on just one Nvidia H100 GPU. |
| Maverick | This is strong in coding and reasoning. It also uses fewer parameters. |
| Behemoth | It is a huge model that’s still in training. Behemoth is targeted at tough STEM tasks. |
Each model targets different needs. Scout is small but mighty, and Maverick was built for more complex jobs. Behemoth is a giant still being trained, but Meta says it’s their most powerful model yet.
What’s So Special About Them?
- They execute tasks with speed. Even Scout can handle tough jobs using less power. That’s because it only needs one GPU.
- The Llama models have displayed high performance. Meta says Scout beats Gemma 3, Mistral 3.1, and Gemini 2.0 Flash-Lite on several well-known tests.
- Maverick delivers high performance with fewer active parameters. That means it thinks faster and costs less to run.
Mixture Of Experts (MoE)
All three Llama 4 models use a special trick called Mixture of Experts (MoE). It’s like having a whole team of AI “experts” ready to help, but only the ones you need step in. This approach saves power and speeds things up. That’s how Llama 4 models can stay big and smart without draining resources.
Are Meta’s Llama Models Better?
- Scout beats other small models on a wide range of tests.
- Maverick performs at the same level, or better, than GPT-4o.
- Behemoth (still training) already shows promise in science and math benchmarks.
Here’s what makes Behemoth stand out:
- 2 trillion total parameters
- 288 billion active parameters used at any one time
- Designed to tackle hard STEM tasks faster and more accurately
Is Llama 4 Open-source?
You can download the models from Meta or Hugging Face. They’re “open-source” but here’s if your product has more than 700 million monthly active users, you need Meta’s permission to use Llama 4.
So technically, it’s not fully open. That’s why the Open Source Initiative argues it doesn’t count as true open-source.
Llama 4 Integrations
- Meta AI on the web
- Messenger
Llama 4 Best Use Cases
- Write content faster
- Translate languages
- Solve math and science questions
- Debug code
- Summarize long articles
- Answer everyday questions
