# Command R\+
##  Cohere — Command R\+
## Model Details
Command R\+ is Cohere's model for complex RAG workflows, multi-step tool use, and enterprise tasks with a 128K context window. For more information about model development and performance, see the [model/service card](https://docs.cohere.com/docs/command-r-plus).
+ **Model launch date:** Aug 2024
+ **Model EOL date:** August 19, 2026
+ **End User License Agreements and Terms of Use:** [View](https://aws.amazon.com/legal/bedrock/third-party-models/)
+ **Model lifecycle:** Legacy
+ **Context window:** 128K tokens
+ **Max output tokens:** 4K
+ **Knowledge cutoff:** Mar 2024
+ **Marketplace product ID:** `prod-nb4wqmplze2pm`
| **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 [Endpoints supported by Amazon Bedrock](endpoints.md) for details.
## Capabilities and Features
***Bedrock Features***
**Features supported using `bedrock-runtime` endpoint**
| **Supported** | **Not Supported** |
| --- | --- |
| +  [Response streaming](/bedrock/latest/APIReference/API_runtime_InvokeModelWithResponseStream.html)
+  [Guardrails](guardrails.html)
+  [Client-side tool calling](tool-use.html) | — |
## Pricing
This model is a third-party model offered and billed through AWS Marketplace. Charges appear on your AWS bill and in AWS Cost Explorer under the model provider (not under Amazon Bedrock). For pricing, 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 | cohere.command-r-plus-v1:0 | https://bedrock-runtime.{region}.amazonaws.com | 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-west-2 (Oregon) |  |  |  |
## 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.
```
pip install boto3
```
**Step 4 - Set environment variables:** Configure your environment to use the API key for authentication.
```
AWS_BEARER_TOKEN_BEDROCK=""
```
**Step 5 - Run your first inference request:** Save the file as `bedrock-first-request.py`
------
#### [ Invoke API ]
```
import json
import boto3
client = boto3.client('bedrock-runtime', region_name='us-east-1')
response = client.invoke_model(
modelId='cohere.command-r-plus-v1:0',
body=json.dumps({
'message': '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='cohere.command-r-plus-v1:0',
messages=[
{
'role': 'user',
'content': [{'text': 'Can you explain the features of Amazon Bedrock?'}]
}
]
)
print(response)
```
------
## See also
* **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon Bedrock. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query bedrock` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).