Using Llama 3.2 1B Instruct on AWS Bedrock
Implementation guide · Llama 3.2 · AI at Meta
Serverless
Open WeightsAWS Bedrock exposes Llama 3.2 1B Instruct through model ID meta.llama3-2-1b-instruct-v1:0. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-10-12. Next refresh: weekly.
Quick Start
- 1
- 2Use the AWS Bedrock SDK or REST API to call
meta.llama3-2-1b-instruct-v1:0— see the documentation for request format. - 3
Code Examples
Install
pip install boto3API key
AWS_ACCESS_KEY_IDModel ID
meta.llama3-2-1b-instruct-v1:0Use 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="meta.llama3-2-1b-instruct-v1:0",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Pricing on AWS Bedrock
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.10 |
| Output tokens | $0.10 |
Capabilities
Structured Outputs
About Llama 3.2 1B Instruct
Llama 3.2 1B Instruct is Meta's Llama 3.2 model. It offers a 128K-token context window with weights openly available for self-hosting and scores 25.6 on GPQA.
Model Specs
Released2024-09-25
Parameters1.23B
Context128K
ArchitectureDecoder Only
Knowledge cutoff2023-12