# NVIDIA Nemotron Nano 9B v2
##  NVIDIA — NVIDIA Nemotron Nano 9B v2
## Model Details
Nemotron Nano 9B v2 is NVIDIA's 9-billion parameter model optimized for efficient text generation, reasoning, and coding on NVIDIA hardware. For more information about model development and performance, see the [model/service card](https://build.nvidia.com/nvidia/nvidia-nemotron-nano-9b-v2/modelcard).
+ **Model launch date:** Aug 18, 2025
+ **EOL no sooner than:** Aug 18, 2026
+ **Legacy period:** at least 6 months
+ **Model lifecycle policy:** [Model lifecycle (For Models Launched Prior to Sept 7 2026)](model-lifecycle-legacy.md)
+ **Model EOL date:** March 30, 2027
+ **End User License Agreements and Terms of Use:** [View](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/)
+ **Model lifecycle:** Legacy
+ **Context window:** 128K tokens
+ **Max output tokens:** 8K
| **Input Modalities** | **Output Modalities** | **[APIs supported](apis.html)** | **[Endpoints supported](endpoints.html)** |
| --- | --- | --- | --- |
|  Audio |  Embedding |  Responses |  bedrock-runtime |
|  Image |  Image |  Chat Completions |  bedrock-mantle |
|  Speech |  Speech |  Invoke | |
|  Text |  Text |  Converse | |
|  Video |  Video | | |
**Tip**
Whenever possible, we recommend using the `bedrock-runtime` endpoint for new applications. See [Inference endpoints supported by Amazon Bedrock](endpoints.md) for details.
## Capabilities and Features
***Bedrock Features***
**Features supported using `bedrock-mantle` endpoint**
| **Supported** | **Not Supported** |
| --- | --- |
| +  [Projects](projects.html)
+  [Client-side tool calling](tool-use.html) | +  [Server-side tool calling](tool-use.html)
+  [Watermarking](watermarking.html) |
**Features supported using `bedrock-runtime` endpoint**
| **Supported** | **Not Supported** |
| --- | --- |
| +  [Response streaming](/bedrock/latest/APIReference/API_runtime_InvokeModelWithResponseStream.html)
+  [Guardrails](guardrails.html)
+  [Model evaluation](evaluation.html)
+  [Prompt management](prompt-management.html)
+  [Flows](flows.html)
+  [Agents](agents.html)
+  [Structured outputs](structured-output.md) | +  [Intelligent prompt routing](prompt-routing.html)
+  [Abuse detection](abuse-detection.html)
+  [Prompt optimization](prompt-management-optimize.html)
+  [Count tokens](count-tokens.html)
+  [Knowledge base](knowledge-base.html)
+  [Watermarking](watermarking.html) |
## Pricing
For pricing information, see the [Amazon Bedrock Pricing](https://aws.amazon.com/bedrock/pricing/) page.
## Programmatic Access
Use the following model IDs and endpoint URLs to access this model programmatically. For more information about the available APIs and endpoints, see [APIs supported](apis.html) and [Endpoints supported](endpoints.html).
| **Endpoint** | **Model ID** | **In-Region endpoint URL** | **Geo inference ID** | **Global inference ID** |
| --- | --- | --- | --- | --- |
| bedrock-runtime | nvidia.nemotron-nano-9b-v2 | https://bedrock-runtime.{region}.amazonaws.com | us-gov.nvidia.nemotron-nano-9b-v2 | Not supported |
| bedrock-mantle | nvidia.nemotron-nano-9b-v2 | https://bedrock-mantle.{region}.api.aws/v1 | Not supported | Not supported |
*For example, if region is us-east-1 (N. Virginia), then the bedrock-runtime endpoint URL will be "https://bedrock-runtime.us-east-1.amazonaws.com" and for bedrock-mantle will be "https://bedrock-mantle.us-east-1.api.aws/v1".*
## Service Tiers
Amazon Bedrock offers multiple service tiers to match your workload requirements. **Standard** provides pay-per-token access with no commitment (set `"service_tier": "default"` or omit the field). **Priority** delivers the fastest response times for a price premium (set `"service_tier": "priority"`). **Flex** provides lower-cost access for flexible, non-time-sensitive workloads (set `"service_tier": "flex"`). **Reserved** provides dedicated throughput with a term commitment for predictable workloads; it is set at the account level rather than per request (contact your AWS account team to enable). For more information, see [service tiers](service-tiers-inference.html).
| **Standard** | **Priority** | **Flex** | **Reserved** |
| --- | --- | --- | --- |
|  |  |  |  |
## Regional Availability
***Regional availability at a glance***
Amazon Bedrock offers three inference options: **In-Region** keeps requests within a single Region for strict compliance, **Geo Cross-Region** routes across Regions within a geography (such as US, EU, and APAC) while respecting data residency, and **Global Cross-Region** routes anywhere worldwide when there are no residency constraints. Refer to the [Regional availability by models](models-region-compatibility.md) page for more details.
| **Region** | **In-Region** | **Geo** | **Global** |
| --- | --- | --- | --- |
| us-east-1 (N. Virginia) |  |  |  |
| us-east-2 (Ohio) |  |  |  |
| us-west-2 (Oregon) |  |  |  |
| eu-south-1 (Milan) |  |  |  |
| eu-west-1 (Ireland) |  |  |  |
| eu-west-2 (London) |  |  |  |
| ap-northeast-1 (Tokyo) |  |  |  |
| ap-south-1 (Mumbai) |  |  |  |
| ap-southeast-2 (Sydney) |  |  |  |
| sa-east-1 (São Paulo) |  |  |  |
| ap-southeast-3 (Jakarta) |  |  |  |
| ap-southeast-4 (Melbourne) |  |  |  |
| ap-northeast-2 (Seoul) |  |  |  |
| ap-southeast-1 (Singapore) |  |  |  |
| us-gov-west-1 (GovCloud) |  |  |  |
| eu-central-1 (Frankfurt) |  |  |  |
| eu-north-1 (Stockholm) |  |  |  |
***Geo CRIS inference details***
**US GovCloud CRIS**
US GovCloud CRIS Inference ID: `us-gov.nvidia.nemotron-nano-9b-v2`
| **Source Region** | **Destination Regions** |
| --- | --- |
| us-gov-west-1 (GovCloud West) | us-gov-west-1 (GovCloud West), us-gov-east-1 (GovCloud East) |
| us-gov-east-1 (GovCloud East) | us-gov-west-1 (GovCloud West), us-gov-east-1 (GovCloud East) |
## Quotas and Limits
Your AWS account has default quotas to maintain the performance of the service and to ensure appropriate usage of Amazon Bedrock. The default quotas assigned to an account might be updated depending on regional factors, payment history, fraudulent usage, and/or approval of a quota [increase request](quotas-increase.html). For more information, see [Quotas for Amazon Bedrock](quotas.md) documentation and see the [limits](/general/latest/gr/bedrock.html#limits_bedrock) for the model.
## Sample Code
**Step 1 - AWS Account:** If you have an AWS account already, skip this step. If you are new to AWS, sign up for an [AWS account](https://portal.aws.amazon.com/billing/signup).
**Step 2 - API key:** Go to the [Amazon Bedrock console](https://console.aws.amazon.com/bedrock/home#/api-keys/long-term/create) and generate a long-term API key.
**Step 3 - Get the SDK:** To use this getting started guide, you must have Python already installed. Then install the relevant software depending on the APIs you are using.
------
#### [ Responses/Chat Completions API ]
```
pip install boto3 openai
```
------
#### [ Invoke/Converse API ]
```
pip install boto3
```
------
**Step 4 - Set environment variables:** Configure your environment to use the API key for authentication.
------
#### [ Responses/Chat Completions API ]
```
OPENAI_API_KEY=""
OPENAI_BASE_URL="https://bedrock-runtime..amazonaws.com/openai/v1"
```
------
#### [ Invoke/Converse API ]
```
AWS_BEARER_TOKEN_BEDROCK=""
```
------
**Step 5 - Run your first inference request:** Save the file as `bedrock-first-request.py`
------
#### [ Chat Completions API ]
```
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="nvidia.nemotron-nano-9b-v2",
messages=[{"role": "user", "content": "Can you explain the features of Amazon Bedrock?"}]
)
print(response)
```
------
#### [ Invoke API ]
```
import json
import boto3
client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
modelId='nvidia.nemotron-nano-9b-v2',
body=json.dumps({
'messages': [{ 'role': 'user', 'content': 'Can you explain the features of Amazon Bedrock?'}],
'max_tokens': 1024
})
)
print(json.loads(response['body'].read()))
```
------
#### [ Converse API ]
```
import boto3
client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.converse(
modelId='nvidia.nemotron-nano-9b-v2',
messages=[
{
'role': 'user',
'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
}
]
)
print(response)
```
------