LLM Reference
AWS Bedrock

Llama 4 Scout 17B on AWS Bedrock

Llama 4 · AI at Meta

ServerlessOpen Source

Last refreshed 2026-05-11. Next refresh: weekly.

Why use Llama 4 Scout 17B on AWS Bedrock?

AWS Bedrock offers Llama 4 Scout 17B with pay-as-you-go pricing at $0.17/1M input tokens. AWS Bedrock is Amazon's fully managed foundation-model service, providing unified API access to top models from Anthropic, Meta, Mistral, and other leading AI labs with built-in tools for RAG, fine-tuning, and AI agent development.

Input / 1M
$0.17
Output / 1M
$0.66
Cache
Not sourced
Batch
-50% · in $0.085 / out $0.33

Setup recipe

Python + curl
Install
pip install boto3
Auth
export AWS_ACCESS_KEY_ID=...
Call
import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
    modelId="llama-4-scout-17b",
Model ID
llama-4-scout-17b

Request example

import boto3

# Reads AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION from env
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
    modelId="llama-4-scout-17b",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])

Gotchas

  • Use Amazon Bedrock model IDs, e.g. "anthropic.claude-3-opus-20240229-v1:0" for on-demand, or cross-region inference profile IDs like "us.anthropic.claude-opus-4-7-20251101-v1:0". These differ from the public model slug.
  • The endpoint template includes a region segment; set the same region in your SDK/client configuration.
  • The examples expect AWS_ACCESS_KEY_ID; rename it only if your application config maps the new variable.

Pricing

TypePrice (per 1M)
Input tokens$0.17
Output tokens$0.66

Capabilities

MultimodalStructured Outputs

About Llama 4 Scout 17B

Multimodal Llama 4 with 16 active experts, supports 10M token context window for long-document processing

FAQ

What does Llama 4 Scout 17B cost on AWS Bedrock?

On AWS Bedrock, Llama 4 Scout 17B costs $0.17 per 1M input tokens and $0.66 per 1M output tokens.

What is the context window for Llama 4 Scout 17B on AWS Bedrock?

Llama 4 Scout 17B supports a 10,000,000 token context window on AWS Bedrock.

Who created Llama 4 Scout 17B?

Llama 4 Scout 17B was created by AI at Meta as part of the Llama 4 model family.

Is Llama 4 Scout 17B open source?

Llama 4 Scout 17B is open source according to the seed data.

Get Started

Model Specs

Released2025-10-01
Parameters17
Context10M
Knowledge cutoff2024-08