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Meta · Llama 4

Llama 4 Scout

Open-weights frontier with a headline 10M-token context.

Llama 4 Scout is a multimodal AI model developed by Meta, designed for both text and image processing. Released in 2023, it is part of the Llama 4 family, positioned to provide high performance and versatility across complex workflows and multimodal tasks.

The model is technically distinguished by its 327,680-token context window, enabling extended-context applications such as document summarization and complex dialogue management. It is optimized for efficient handling of structured and unstructured data, with a pricing structure aimed at balancing enterprise-grade functionality and cost-effectiveness.

Llama 4 Scout occupies a middle-tier position in the Llama 4 family, balancing affordability and advanced functionality. Compared to its predecessors, it introduces an expanded context window and improved multimodal processing, making it a versatile option for diverse application scenarios.

Background

Llama is a family of large language models (LLMs) released by Meta AI starting in February 2023.

Wikipedia

Specs

Context window
328K tokens
Max output
16K tokens
Input ($/1M tokens)
$0.080
Output ($/1M tokens)
$0.300
Modalities
Text · Image
Released
Apr 5, 2025
Weights
Open

Pricing last synced Apr 27, 2026 via OpenRouter. Confirm against official docs before committing.

Capabilities

  • Tool use
  • Vision
  • Extended thinking
  • Prompt caching
  • Open weights

What it excels at

  • Large context window

    Processes up to 327,680 tokens, enabling extensive contextual understanding of long-form content.

  • Multimodal capability

    Processes both text and image inputs for versatile applications.

  • Cost efficiency

    Balances performance with affordable input and output pricing.

  • Contextual understanding

    Excels in maintaining context within large datasets or extended workflows.

When to use this model

  • →Document summarization — The large context window effectively handles summarization of extensive documents.
  • →Multimodal chatbots — Supports conversations that require processing both text and image inputs.
  • →Content creation — Facilitates the generation of text and image-rich materials in cohesive workflows.
  • →Customer support — Handles multi-turn dialogues with memory of extensive prior context.

Analysis synthesized from gpt-4o, llama-4-maverick, phi-4, etc.

API model id

meta-llama/Llama-4-Scout

Vendor docs: www.llama.com

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