Meta's latest advancements in AI technology have led to the development of the Llama 4 models, with two models, Scout and Maverick, being open-sourced for public use. These models are part of the "Llama 4 herd," each designed for specific purposes, from efficient deployment to enterprise-level reasoning.
The Scout model is a lightweight and fast model, ideal for developers and researchers with limited GPU resources. It's perfect for applications like long-context memory chatbots, code summarization tools, and educational Q&A bots. With 109B parameters and 17B active parameters, Scout has a 10M context-length window and supports up to 8 images in a single prompt.
On the other hand, the Maverick model is a flagship model designed for advanced reasoning, coding, and multimodal applications. It's suitable for AI pair programming, enterprise-level document understanding, and educational tutoring systems. With 400B parameters and 17B active parameters, Maverick has a 1M context-length window and outperforms GPT-4o and Gemini 2.0 Flash in benchmark tests.
Meta's largest model, Behemoth, is not publicly available but is used as a teacher model for internal training and benchmarking. The Llama 4 models have achieved impressive benchmark results, with Maverick scoring an ELO score of 1417 on the LMSYS Chatbot Arena and outperforming GPT-4o and Gemini 2.0 Flash in coding, reasoning, and multilingual tasks.
The Llama 4 models are optimized for NVIDIA GPUs, with TensorRT-LLM delivering over 40K tokens per second on NVIDIA Blackwell B200 GPUs. This makes them suitable for a wide range of applications, from research to enterprise use cases.
You can access Llama 4 Scout and Maverick through (link unavailable), Hugging Face, or Meta's apps like WhatsApp and Instagram via the Meta AI assistant. With their impressive performance and versatility, the Llama 4 models are set to revolutionize the field of AI technology.
