Model Directory› Meta› Llama 4 Scout
Meta BalancedOpen weights

Llama 4 Scout

A smaller open-weight MoE sibling built around an enormous context window, aimed at whole-codebase and whole-corpus workloads on a single node.

At a glance

Released
Feb 10, 2026
Provider
Meta
Context window
10,000,000 tokens
Max output
16,000 tokens
Modalities
Text + image → text
Knowledge cutoff
August 2025
API model ID
llama-4-scout
License
Open weights (Llama 4 Community License)

Pricing

Standard
Input$0.10 / 1M
Output$0.40 / 1M

* Rates are from a third-party aggregator — verify before relying on them. A typical 1,500-token prompt with a 650-token answer costs ≈ $0.0004 on the standard tier. Run your own prompt through the calculator →

What's new vs the previous model

Compared with Llama 3.2 11B (September 2024)
  • Ten-million-token context unlocks whole-repository reasoning
  • Efficient MoE routing keeps it affordable to run
  • Lower peak quality than Maverick on the hardest tasks

Best use cases

Whole-codebase analysis

Loads entire repositories into context for review and refactoring.

Long-document synthesis

Reasons across books, filings, or massive log dumps in one pass.

Edge-of-datacenter serving

Fits on a single node while still offering huge context.

Strengths & limitations

Strengths

  • Massive context
  • Cheap
  • Open weights

Limitations

  • Quality dips as context fills
  • Below the flagship on hard reasoning

How to test it

  1. No-code: open meta.ai and pick Llama 4 Scout from the model switcher — no API key needed.
  2. Playground: sign in to llama.com (download the weights) and run prompts in the workbench, then copy the generated code.
  3. API: pick an inference host (Together, Fireworks, Groq, AWS Bedrock…), create a key and call its OpenAI-compatible endpoint, or read the docs.
# via an OpenAI-compatible inference host (Together, Fireworks, Groq, …)
curl https://<your-host>/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "llama-4-scout", "messages": [{"role": "user", "content": "Explain tokenization in one paragraph."}]}'

Where to get access

Consumer app

Chat with Llama 4 Scout in Meta AI (meta.ai, WhatsApp, Instagram, Messenger).

meta.ai ↗

Direct API

Pay-as-you-go access via llama.com (download the weights).

llama.com (download the weights) ↗

Also available

Hosted by Together, Fireworks, Groq, AWS Bedrock and others.

llama.meta.com ↗

Developer docs

API reference, SDKs and quickstarts for Meta.

llama.meta.com/docs ↗