> This page is for version v2 API (default).
> For other versions, use one of these documentation indexes:
> - v2 API (default): https://docs.cohere.com/v2/llms.txt
> - v1 API: https://docs.cohere.com/v1/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.cohere.com/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.cohere.com/_mcp/server.

# Command R: Retrieval-Augmented Generation at Scale

> Command R: Retrieval Augmented Generation at scale.

Today, we are introducing Command R, a new LLM aimed at large-scale production workloads. Command R targets the emerging “scalable” category of models that balance high efficiency with strong accuracy, enabling companies to move beyond proof of concept, and into production.

Command R is a generative model optimized for long context tasks such as retrieval-augmented generation (RAG) and using external APIs and tools. It is designed to work in concert with our industry-leading Embed and Rerank models to provide best-in-class integration for RAG applications and excel at enterprise use cases. As a model built for companies to implement at scale, Command R boasts:

* Strong accuracy on RAG and Tool Use
* Low latency, and high throughput
* Longer 128k context and lower pricing
* Strong capabilities across 10 key languages
* Model weights available on HuggingFace for research and evaluation

For more information, check out the [official blog post](https://cohere.com/blog/command-r/) or the [Command R documentation](/docs/command-r).