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 titan-multimodal-embeddings-g1. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the AWS Bedrock SDK or REST API to call
titan-multimodal-embeddings-g1— see the documentation for request format.
Code Examples
Install
pip install boto3API key
AWS_ACCESS_KEY_IDModel ID
titan-multimodal-embeddings-g1Use 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="titan-multimodal-embeddings-g1",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
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.
Model Specs
Released2023-11-01