Home › Language Models › Llama 4 Maverick & Scout

Llama 4 Maverick & Scout - AI Language Models Tool

Overview

Llama 4 Maverick & Scout are Meta's next-generation Mixture-of-Experts language models released on Hugging Face. Maverick (~400B total, 17B active parameters, 128 experts) and Scout (~109B total, 17B active parameters, 16 experts) provide native multimodal input and very long context support. Both models integrate with Hugging Face transformers and TGI for deployment, enabling multimodal (text + image) applications and extended-context workflows, including Scout's support for context lengths up to 10 million tokens.

Key Features

  • Mixture-of-Experts architecture for sparse activation
  • Maverick: ~400B total, 17B active parameters, 128 experts
  • Scout: ~109B total, 17B active parameters, 16 experts
  • Native multimodal inputs: text and images
  • Scout supports context lengths up to 10 million tokens
  • Integrated with Hugging Face transformers and TGI for deployment

Ideal Use Cases

  • Multimodal assistants that process text and images
  • Document analysis and summarization with long context
  • Retrieval-augmented generation across large knowledge bases
  • Research into MoE architectures and scaling
  • High-context conversational agents and long-form generation

Getting Started

  • Read the Llama 4 release notes on the Hugging Face blog
  • Visit the Hugging Face model pages for Maverick and Scout
  • Install Hugging Face transformers and TGI packages
  • Choose Maverick or Scout based on context and cost needs
  • Load the selected model using transformers or TGI APIs
  • Prepare multimodal inputs (text and images) for inference
  • Test inference with short prompts before scaling

Pricing

Pricing and licensing information not disclosed in the provided source. Check Hugging Face model pages or Meta announcements for availability and pricing.

Limitations

  • Very large total model sizes imply significant compute requirements
  • MoE routing adds implementation and deployment complexity
  • Extremely long contexts may require specialized memory and tooling

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
Visit Official Website

Related Tools

Qwen2.5-7B

Qwen2.5-7B is a large language model designed for text generation, featuring improvements in coding, mathematics, instruction following, long text generation, and multilingual support. It supports context lengths up to 128K tokens and is intended for sophisticated NLP tasks.
DeepSeek-V3

An open-source language model from deepseek-ai offering efficient long-context inference with native sparse attention and support for multiple precisions.
Llama 3

Llama 3 is an open access large language model (LLM) released by Meta, available in various configurations (8B and 70B parameters) with capabilities for fine-tuning and integrations into platforms like Hugging Face, Google Cloud, and Amazon SageMaker.
UNfilteredAI-1B

A large-scale text generation model designed for creative and unconstrained content production without traditional filtering.
FLUX1.1 [pro]

A new text-to-image AI model capable of generating images six times faster than its predecessor, with higher quality, better prompt adherence, and more diversity in outputs. It includes a prompt upsampling feature that utilizes a language model to enhance prompts for improved image generation.
Shuttle-3

Shuttle-3 is a state-of-the-art language model designed for high-quality text generation, particularly suited for complex chat, multilingual communication, and reasoning tasks. It is fine-tuned from the Qwen-2.5-72b-Instruct model and designed to emulate high-quality prose similar to Claude 3 models.