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Llama 4 Scout

by Meta

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimo

L4

Models

Llama 4 Scout

Added 10 July 2026

#meta-llama

Overview

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

Best for

Best for
Open-weight long-context coding on a budget

Use cases

  • repo Q&A
  • self-host experiments
  • batch coding

How to use / API access

Call via OpenRouter with model id `meta-llama/llama-4-scout`.

  • openrouter · meta-llama/llama-4-scout Docs

OpenRouter id: meta-llama/llama-4-scout

Benchmarks

  • Intelligence Index (artificial-analysis) : 10 index
  • Coding Index (artificial-analysis) : 8.2 index
  • Agentic Index (artificial-analysis) : 1.1 index
  • Design Arena codecategories (other) : 826 elo · #111
  • Design Arena dataviz (other) : 932 elo · #103
  • Design Arena gamedev (other) : 831 elo · #110
  • Design Arena uicomponent (other) : 810 elo · #106

Enterprise DNA angle

Omni helps teams prove Scout quality on real jobs before committing infra.

Notes

Llama 4 Scout is listed in the EDNA Models directory from the OpenRouter catalogue.

Pros

  • Open-weights economics with long context
  • Good fit for cost-controlled coding agents

Cons

  • Hosted quality varies by endpoint
  • May need eval gates vs closed frontier models
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