Using Titan Text Express on AWS Bedrock
Implementation guide · Titan · Amazon Web Services (AWS) AI
AWS Bedrock exposes Titan Text Express through model ID titan-text-express. 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-text-express— see the documentation for request format. - 3
Code Examples
pip install boto3AWS_ACCESS_KEY_IDtitan-text-expressUse 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-text-express",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.60 |
Capabilities
About Titan Text Express
Amazon Titan Text Express is a large language model (LLM) crafted by AWS, offering a balance of price and performance for text generation 123. As part of the Amazon Titan family, this versatile model excels in tasks such as open-ended text generation, conversational chat, and Retrieval Augmented Generation (RAG) 124. It supports a context length of up to 8,000 tokens, enabling it to handle extensive text inputs effectively 235. While optimized for English, it provides preview support for over 100 other languages 235.