Command R+
Cohere's most powerful Command model, optimized for complex enterprise workloads requiring advanced reasoning, RAG, and multi-step tool use.
Cohere 
Amazon Bedrock Enterprise RAG and multi-step tool use
Command R+ is a large language model developed by Cohere, positioned as the company's flagship text generation model for enterprise use. It is available through Amazon Bedrock, allowing organizations to deploy it within AWS's managed cloud infrastructure. The model supports a 128,000-token context window and was trained on data up to January 2023. It is designed specifically for demanding enterprise workloads that require high accuracy and reliability.
What distinguishes Command R+ is its purpose-built support for retrieval-augmented generation, enabling it to ground responses in external knowledge sources rather than relying solely on parametric memory. It also supports multi-step tool use and agentic workflows, allowing it to interact with APIs, databases, and other external systems. The model handles multiple languages, making it applicable for global deployments. It is best suited for production applications such as intelligent search, document summarization, customer support automation, and complex data analysis pipelines.
What Command R+ supports
Retrieval-Augmented Generation
Purpose-built to integrate with external knowledge sources, allowing responses to be grounded in real retrieved data rather than model memory alone.
Multi-Step Tool Use
Supports agentic workflows where the model can call APIs, query databases, and chain multiple tool interactions autonomously across a single task.
Advanced Reasoning
Handles complex multi-step reasoning tasks including question answering, analysis, and decision support across long-form inputs.
Long Context Window
Processes up to 128,000 tokens in a single context, enabling analysis of lengthy documents, transcripts, or multi-document inputs.
Multilingual Output
Understands and generates text across multiple languages, supporting enterprise deployments that serve international users.
Text Generation
Generates structured and unstructured text for use cases such as summarization, drafting, classification, and data extraction.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 43.2% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 32.3% |
| MATH-500 | Undergraduate and competition-level math problems | 27.9% |
| AIME 2024 | American math olympiad problems | 0.7% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 12.2% |
| HLE | Questions that challenge frontier models across many domains | 4.5% |
| SciCode | Scientific research coding and numerical methods | 11.8% |
Common questions about Command R+
What is the context window for Command R+?
Command R+ supports a context window of 128,000 tokens, allowing it to process large documents or extended conversation histories in a single request.
What is the training data cutoff for Command R+?
According to the model metadata, the training data cutoff is January 2023. The model does not have knowledge of events after that date unless provided via retrieval or context.
How is Command R+ accessed on MindStudio?
Command R+ is available on MindStudio via Amazon Bedrock. No separate API key setup is required to use it within MindStudio.
What types of tasks is Command R+ best suited for?
Command R+ is designed for enterprise workloads including retrieval-augmented generation, multi-step tool use, intelligent search, document summarization, customer support automation, and complex data analysis pipelines.
Does Command R+ support tool use and agentic workflows?
Yes. Command R+ supports multi-step tool calling, enabling it to interact with external APIs, databases, and other systems as part of agentic workflows.
What people think about Command R+
Community discussion around Cohere's Command R series reflects that the model was widely used as a daily driver by many users roughly two years ago, particularly valued for its RAG capabilities and enterprise focus. Cohere as a company continues to attract attention, having been valued at $6.8 billion in a recent fundraising round.
Some community members have noted uncertainty about the ongoing trajectory of the Command R and Command A model lines, with questions about how they fit into Cohere's current product strategy. Discussions are generally informational rather than critical, with no widespread technical complaints surfacing in the sampled threads.
What ever happened to Cohere’s Command-R and Command-A series of models? R was a lot of folks’ daily driver model like 2 years ago.
GPT -OSS is heavily trained on benchmark. scored rank 34 on simplebench worse than grok 2
AI startup Cohere valued at $6.8 billion in latest fundraising, hires Meta exec
Parameters & options
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