Meta Llama 4 Release Date and Model History: Comparing Llama 4 Scout, Maverick, Gemma 3, and Mistral Small
Meta released Llama 4 Scout and Llama 4 Maverick on April 5, 2025, making Llama 4 the first public Llama family built around native multimodal input and mixture of experts design [source: Meta]. The short version: Scout is the long context workhorse, Maverick is the stronger general model, and both now compete with compact rivals like Gemma 3 and Mistral Small.
Llama model history in one quick pass
The Llama line started in 2023 as Meta’s answer to closed AI labs. Llama 1 was mostly for researchers. Llama 2 made the family far more usable for apps and chat. Llama 3 raised the bar with better reasoning, cleaner text, and strong open weight adoption.
Then came Llama 4. This was not just another size bump. Meta moved to a mixture of experts setup. That means only part of the model is active for each request. In theory, you get stronger answers without paying the full compute cost every time.
The catch is that MoE models can be annoying to serve. Some tools support them well. Some do not. Expect to waste time checking inference engines, memory limits, and quantized versions before you get smooth results.
Llama 4 Scout vs Llama 4 Maverick
- Llama 4 Scout: Built for massive context. It is the model to watch for long documents, code review, archives, and research workflows.
- Llama 4 Maverick: Built for stronger everyday intelligence. It fits chatbots, coding assistants, image reasoning, and multi step tasks.
- Llama 4 Behemoth: Meta also discussed this larger model, but Scout and Maverick were the practical public focus at launch.
Scout’s headline feature is its very long context window. That matters if you want to feed the model far more than a normal prompt. Think product docs, Slack exports, or a whole repo. Maverick is the better pick when answer quality matters more than stuffing in a huge file.
How Gemma 3 fits in
Gemma 3 is Google’s open model family from March 2025. It comes in several sizes, including 1B, 4B, 12B, and 27B. The bigger versions support images and a 128K context window [source: Google].
Gemma 3 is not trying to win only by size. Its appeal is practical. The 27B model can be a strong choice for teams that need good answers but do not want a heavy server bill. The smaller versions are useful for local apps, private tools, and edge cases where speed matters.
Honestly, it feels like Gemma’s biggest win is how normal it is to run. Less drama. Fewer giant hardware demands. That counts when you are the person paying the cloud invoice.
Where Mistral Small stands
Mistral Small 3.1 is a compact 24B model with text and vision support. It also offers a 128K context window and is known for fast responses, especially for its size [source: Mistral AI].
Mistral Small is the “just get it done” option. It is not as flashy as Llama 4 Maverick. It does not have Scout’s monster context. But it is often easier to deploy, easier to test, and easier to fit into a real product.
Side by side comparison
| Model | Best use | Main strength | Main tradeoff |
|---|---|---|---|
| Llama 4 Scout | Long documents, research, codebases | Huge context capacity | Serving can be tricky |
| Llama 4 Maverick | Chat, agents, coding, images | Strong general performance | Heavier than compact rivals |
| Gemma 3 | Affordable apps, local tools | Wide size range | Less powerful at the low end |
| Mistral Small | Fast production assistants | Good speed for 24B | Not built for giant context |
Which model should you choose?
- Choose Llama 4 Scout if your app needs to read a huge amount of text at once.
- Choose Llama 4 Maverick if you want the best Llama 4 option for broad AI assistant tasks.
- Choose Gemma 3 if you need a flexible open model family with smaller deployment options.
- Choose Mistral Small if speed, cost, and simple production use matter most.
Bottom line: Llama 4 is a major step for Meta because it adds native multimodal ability and MoE design. Scout and Maverick are exciting, but they are not automatic wins for every team. If your app is small, private, or cost sensitive, Gemma 3 and Mistral Small may save you plenty of headaches.
