Using NVIDIA Nemotron Nano 9B v2 on AWS Bedrock

Implementation guide · NVIDIA Nemotron Nano 12B v2 VL · NVIDIA AI

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AWS Bedrock exposes NVIDIA Nemotron Nano 9B v2 through model ID nvidia-nemotron-nano-9b-v2. 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. 1
    Create an account at AWS Bedrock and generate an API key.
  2. 2
    Use the AWS Bedrock SDK or REST API to call nvidia-nemotron-nano-9b-v2 — see the documentation for request format.
  3. 3
    You'll be billed $0.06/1M input, $0.23/1M output tokens. See full pricing.
API PortalDocumentationPricing

Code Examples

Install
pip install boto3
API key
AWS_ACCESS_KEY_ID
Model ID
nvidia-nemotron-nano-9b-v2

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="nvidia-nemotron-nano-9b-v2",
    messages=[{
        "role": "user",
        "content": [{"text": "Hello"}]
    }]
)
print(response["output"]["message"]["content"][0]["text"])

Pricing on AWS Bedrock

TypePrice (per 1M)
Input tokens$0.06
Output tokens$0.23

Capabilities

Structured Outputs

About NVIDIA Nemotron Nano 9B v2

NVIDIA Nemotron Nano 9B v2 is NVIDIA AI's NVIDIA Nemotron Nano 12B v2 VL model. Its knowledge cutoff is 2025-03.

Full model details →

Model Specs

Released2025-12-01
Parameters9B
Knowledge cutoff2025-03

Provider

AWS Bedrock

Amazon Web Services

Seattle, Washington, United States