Last refreshed 2026-06-15. Next refresh: weekly.
Why use Command R+ on AWS Bedrock?
AWS Bedrock offers Command R+ with pay-as-you-go pricing at $3.00/1M input tokens. AWS Bedrock is Amazon's fully managed foundation-model service, providing unified API access to top models from Anthropic, Meta, Mistral, and other leading AI labs with built-in tools for RAG, fine-tuning, and AI agent development.
Compare Command R+ across 6 providers to find the best fit for your use caseSetup recipe
Python + curlpip install boto3export AWS_ACCESS_KEY_ID=...import boto3
client = boto3.client("bedrock-runtime", region_name="us-east-1")
response = client.converse(
modelId="command-r-plus",command-r-plusRequest example
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="command-r-plus",
messages=[{
"role": "user",
"content": [{"text": "Hello"}]
}]
)
print(response["output"]["message"]["content"][0]["text"])Gotchas
- 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.
- The endpoint template includes a region segment; set the same region in your SDK/client configuration.
- The examples expect AWS_ACCESS_KEY_ID; rename it only if your application config maps the new variable.
Compare Command R+ Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Cohere API | $2.50 | $10.00 |
| AWS Bedrock | $3.00 | $15.00 |
| Microsoft Foundry | $3.00 | $15.00 |
| OCI Generative AI | — | — |
| OpenRouter | $2.50 | $10.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $3.00 |
| Output tokens | $15.00 |
Capabilities
About Command R+
Command R+ is a powerful large language model from Cohere, tailored for robust enterprise applications. It features an architecturally impressive 104 billion parameters and a 128k-token context window, allowing it to adeptly manage complex tasks and long dialogue sessions. Its cutting-edge capabilities include retrieval-augmented generation (RAG) with inline citations, multilingual functionality supporting ten major languages, and multi-step tool usage to automate complex workflows. The model is suited for diverse business operations such as financial analysis, customer support, and content creation, and can be accessed via Cohere's API or through platforms like Microsoft Azure and Oracle Cloud Infrastructure.