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Llama 4 Maverick & Scout - AI Language Models Tool

Overview

Llama 4 Maverick & Scout are Meta's new Mixture-of-Experts language models published via Hugging Face. Maverick (~400B total, 17B active, 128 experts) and Scout (~109B total, 17B active, 16 experts) support native multimodal inputs (text and images) and very long contexts. Both models integrate with Hugging Face transformers and TGI for deployment. Scout is highlighted for extremely long context lengths (up to 10 million tokens).

Key Features

  • Mixture-of-Experts architecture with Maverick and Scout variants
  • Maverick: ~400B total, 17B active parameters, 128 experts
  • Scout: ~109B total, 17B active parameters, 16 experts
  • Native multimodal input support for text and images
  • Extremely long context lengths — Scout up to 10M tokens
  • Integrates with Hugging Face transformers and TGI for deployment
  • Active-parameter inference via expert routing

Ideal Use Cases

  • Multimodal assistants combining text understanding and image interpretation
  • Long-document summarization, analysis, and retrieval-augmented generation
  • Research and experimentation with Mixture-of-Experts architectures
  • Deployments requiring very long context or sparse expert routing
  • Prototyping models with extremely large context memory needs

Getting Started

  • Read the Hugging Face Llama 4 release blog post
  • Install Hugging Face transformers and TGI libraries
  • Locate the Maverick or Scout model pages on Hugging Face
  • Review model license, hardware, and inference requirements
  • Follow repository instructions to download and deploy models

Pricing

Pricing not disclosed in the provided information.

Limitations

  • No pricing information provided in the tool context
  • Hardware and inference cost details are not provided
  • Model license and usage terms are not specified in the provided information

Key Information

  • Category: Language Models
  • Type: AI Language Models Tool
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