Using Gemma 4 31B on AWS Bedrock
Implementation guide · Gemma 4 · Google DeepMind
ServerlessOpen Source
AWS Bedrock exposes Gemma 4 31B through model ID gemma-4-31b. 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
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Code Examples
Install
pip install boto3API key
AWS_ACCESS_KEY_IDModel ID
gemma-4-31bUse 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="gemma-4-31b",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
Capabilities
VisionMultimodalJSON / Tool use
About Gemma 4 31B
Dense 31B model bridging the gap between server-grade performance and local execution. Ranks #3 on Arena AI leaderboard. Supports text, image, and video inputs with advanced reasoning.
Model Specs
Released2026-03-31
Parameters31B
Context256k
Knowledge cutoff2025-01