LLM Reference
AWS Bedrock

Llama 4 Scout 17B-16E Instruct on AWS Bedrock

Llama 4 · AI at Meta

ServerlessOpen Weights

Last refreshed 2026-06-04. Next refresh: weekly.

Why use Llama 4 Scout 17B-16E Instruct on AWS Bedrock?

AWS Bedrock offers Llama 4 Scout 17B-16E Instruct 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.

Compare Llama 4 Scout 17B-16E Instruct across 11 providers to find the best fit for your use case
Input / 1M
$0.17
Output / 1M
$0.22
Cache
Not sourced
Batch
Not sourced

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-16e-instruct",
Model ID
llama-4-scout-17b-16e-instruct

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-16e-instruct",
    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.

Compare Llama 4 Scout 17B-16E Instruct Across Providers

ProviderInput (per 1M)Output (per 1M)
Cloudflare Workers AI$0.27$0.85
OpenRouter$0.08$0.30
Together AI
Fireworks AI
DeepInfra$0.08$0.30
View all 11 providers →

Pricing

TypePrice (per 1M)
Input tokens$0.17
Output tokens$0.22

Capabilities

VisionMultimodalStructured Outputs

About Llama 4 Scout 17B-16E Instruct

Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.

FAQ

What does Llama 4 Scout 17B-16E Instruct cost on AWS Bedrock?

On AWS Bedrock, Llama 4 Scout 17B-16E Instruct costs $0.17 per 1M input tokens and $0.22 per 1M output tokens.

What is the context window for Llama 4 Scout 17B-16E Instruct on AWS Bedrock?

Llama 4 Scout 17B-16E Instruct supports a 328k token context window on AWS Bedrock.

How does AWS Bedrock compare to other Llama 4 Scout 17B-16E Instruct providers?

Llama 4 Scout 17B-16E Instruct is available from 11 providers. The cheapest input pricing is $0.08/1M tokens from OpenRouter.

Who created Llama 4 Scout 17B-16E Instruct?

Llama 4 Scout 17B-16E Instruct was created by AI at Meta as part of the Llama 4 model family.

Is Llama 4 Scout 17B-16E Instruct open source?

Llama 4 Scout 17B-16E Instruct has open weights under Llama 3 Community according to the seed data, but that does not necessarily mean an OSI-approved open-source license.

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