LLM Reference
AWS Bedrock

Using Llama 3.3 70B Instruct on AWS Bedrock

Implementation guide · Llama 3.3 · AI at Meta

ServerlessOpen Weights

AWS Bedrock exposes Llama 3.3 70B Instruct through model ID meta.llama3-3-70b-instruct-v1:0. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-07-09. Next refresh: weekly.

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 meta.llama3-3-70b-instruct-v1:0 — see the documentation for request format.
  3. 3
    You'll be billed $0.72/1M input, $0.72/1M output tokens. See full pricing.
API PortalDocumentationPricingModel Card

Code Examples

Install
pip install boto3
API key
AWS_ACCESS_KEY_ID
Model ID
meta.llama3-3-70b-instruct-v1:0

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="meta.llama3-3-70b-instruct-v1:0",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])

Pricing on AWS Bedrock

TypePrice (per 1M)
Input tokens$0.72
Output tokens$0.72

Capabilities

Structured Outputs

About Llama 3.3 70B Instruct

Llama 3.3 70B Instruct is Meta's Llama 3.3 model. It offers a 128K-token context window with weights openly available for self-hosting.

Full model details →

Model Specs

Released2025-09-01
Parameters70B
Context128k
Knowledge cutoff2023-12

Provider

AWS Bedrock
AWS Bedrock

Amazon Web Services

Seattle, Washington, United States