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Llama 4 Scout

Llama 4 Scout is a Meta model with 10M context, Not verified in / Not verified out per million tokens, last verified September 4, 2026. Open weights: yes. Public-board scores are linked to the publisher; vendor-only figures stay in the watch-out, not on the board.

Llama 4 Scout is Meta's open-weight 109B/17B MoE with a 10M-token extended context (maintenance-mode — Meta ended Llama development for Muse).

Catalog record checked September 4, 2026Individual provider fields may change

AI model specification details
SpecificationLlama 4 Scout
ProviderMeta
TierBudget
Context window10M
Max output131K
Input / 1M tokensNot verifiedUnverified
Output / 1M tokensNot verifiedUnverified
WeightsOpen
Parameters109B total / 17B active (MoE)
Reasoning levelsNot verifiedUnverified
Modalitiestext, image
LicenseLlama 4 Community License
API model idllama-4-scout
ReleasedApril 5, 2025

Pricing tiers: Open-weight (Llama 4 Community License) — self-host free; 10M-token context via iRoPE (256K pretrained, length-generalised). No first-party Meta API: the Llama API Public Preview was retired 2026-07-06; Meta's endpoint serves Muse models only.

Verified evidence

Published benchmark results

Each result keeps its source and measurement date visible. A missing benchmark is not treated as a zero.

Published benchmark results for Llama 4 Scout
BenchmarkScoreMeasuredSource
Artificial Analysis Intelligence Index402026-08-14Artificial Analysis · View source

Best for

  • Very long-context retrieval
  • Open-weight self-hosting
  • Single-GPU (int4)

Watch out

10M context is extended capability; practical use starts at 256K pretrained window. Meta ended Llama development for the Muse family, and Groq retired its Scout endpoint on 2026-07-17 — treat Llama 4 as maintenance-mode open weights.

Source receipts

Catalog figures for this model were checked against the following sources.

Common questions

Llama 4 Scout

Answered from the verified figures on this page rather than general guidance.

What is Llama 4 Scout's context window?

Llama 4 Scout accepts about 10M tokens of context. That only matters if you routinely send very long documents, large codebases, or multi-turn histories that approach that limit.

What is Llama 4 Scout best for?

Llama 4 Scout is a budget tier from Meta. It suits very long-context retrieval, open-weight self-hosting, single-gpu (int4). 10M context is extended capability; practical use starts at 256K pretrained window. Meta ended Llama development for the Muse family, and Groq retired its Scout endpoint on 2026-07-17 — treat Llama 4 as maintenance-mode open weights.

Can I self-host Llama 4 Scout?

Llama 4 Scout publishes open weights, but self-hosting depends on the licence, hardware footprint, quantisation quality, and serving stack. A hosted API is often cheaper until you have measured throughput and concurrency on your own hardware.