Using Amazon Titan Multimodal Embeddings G1 on AWS Bedrock

Implementation guide · Titan · Amazon Web Services (AWS) AI

Serverless

AWS Bedrock exposes Amazon Titan Multimodal Embeddings G1 through model ID amazon.titan-embed-image-v1. Use the setup steps, capabilities, and official provider links below to validate this route before deployment.

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Quick Start

  1. 1
    Create an account at AWS Bedrock and generate an API key.
  2. 2
    Use the AWS Bedrock SDK or REST API to call amazon.titan-embed-image-v1 — see the documentation for request format.

Code Examples

Install
pip install boto3
API key
AWS_ACCESS_KEY_ID
Model ID
amazon.titan-embed-image-v1

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="amazon.titan-embed-image-v1",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])

Capabilities

No model capability flags are currently sourced.

About Amazon Titan Multimodal Embeddings G1

Amazon Titan Multimodal Embeddings G1 is Amazon's Titan model. It was released 2023-11-01.