Using Llama 3.2 11B Vision on AWS Bedrock

Implementation guide · Llama 3.2 · AI at Meta

ServerlessOpen Weights

AWS Bedrock exposes Llama 3.2 11B Vision through model ID llama-3.2-11b-vision. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-07-09. Next refresh: weekly.

Quick Start

1
Create an account at AWS Bedrock and generate an API key.
2
Use the AWS Bedrock SDK or REST API to call llama-3.2-11b-vision — see the documentation for request format.
3
You'll be billed $0.20/1M input, $0.27/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install boto3

API key

AWS_ACCESS_KEY_ID

Model ID

llama-3.2-11b-vision

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.

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-3.2-11b-vision",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])