Llama 4 Scout 17B
llama-4-scout-17b
Last refreshed 2026-05-11. Next refresh: weekly.
Llama 4 Scout 17B is worth evaluating for rag, long context, and vision when its provider route and context window match the workload.
Decision context: RAG task fit, 1 tracked provider route, and research from 2026-04-19.
Use it for
- Teams evaluating rag, long context, and vision
- Workloads that can use a 10M context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Workloads where another current model has stronger sourced task evidence
Cheapest output
$0.660
AWS Bedrock per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-04-19
Researched 32d ago
Top use-case fit
RAG
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Vision
Included by capability and metadata signals in the decision map.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Batch in / out | Route |
|---|---|---|---|---|
| AWS Bedrock | $0.170 | $0.660 | $0.085 / $0.330 | Serverless |
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Multimodal Llama 4 with 16 active experts, supports 10M token context window for long-document processing
Llama 4 Scout 17B has a 10M-token context window.
Llama 4 Scout 17B input tokens at $0.17/1M, output at $0.66/1M.
Capabilities
Rankings
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Large-scale open-source AI for social technologies.