Llama 4 Scout 17B Instruct
llama-4-scout-17b-instruct
Last refreshed 2026-05-19. Next refresh: weekly.
Llama 4 Scout 17B Instruct is worth evaluating for coding, rag, and long context when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-05-19.
Use it for
- Teams evaluating coding, rag, and long context
- 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
$0.660
AWS Bedrock per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Grade C
Ranked by benchmark score divided by cheapest output price
Freshness
2026-05-19
Researched 2d ago
Top use-case fit
Coding
Q/$ C1 relevant benchmark in the decision map.
RAG
Included by capability and metadata signals in the decision map.
Long context
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 Coding
Migration checks
No linked migration route is available for this model yet.
About
Llama 4 Scout 17B Instruct is Meta's Llama 4 model with multimodal text and image input. It scores 1295 on the Chatbot Arena benchmark.
Llama 4 Scout 17B Instruct has a 10M-token context window.
Llama 4 Scout 17B Instruct input tokens at $0.17/1M, output at $0.66/1M.
Capabilities
Benchmark Scores(4)
| Benchmark | Score | Version | Source |
|---|---|---|---|
| Chatbot Arena | 1295.0 | — | https://lmarena.ai |
| Massive Multi-discipline Multimodal Understanding | 69.4 | — | https://ai.meta.com/blog/llama-4-scout-maverick/ |
| MMLU PRO | 74.3 | — | https://ai.meta.com/blog/llama-4-scout-maverick/ |
| LiveCodeBench | 32.8 | — | https://ai.meta.com/blog/llama-4-scout-maverick/ |
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