Command R+ is a cutting-edge large language model designed for enterprise applications, focusing on advanced capabilities such as Retrieval-Augmented Generation (RAG) and multi-step tool use. It is built to enhance efficiency and accuracy in real-world business scenarios.
Command R+ is tailored for enterprise scenarios such as customer support, finance, human resources, and marketing. It is particularly effective in applications requiring complex reasoning and automation.
The model supports multiple languages and has been evaluated in ten primary languages while also incorporating training data from thirteen additional languages.
Command R+ utilizes an optimized transformer architecture that is auto-regressive. It employs a combination of supervised fine-tuning (SFT) and preference training to align its outputs with human preferences regarding helpfulness and safety.
The model was trained on a diverse dataset that includes a wide variety of texts across multiple domains.
Cohere has not specified the exact sources or total size of the training data but emphasizes its diversity to enhance the model's understanding and reduce biases.
The model's knowledge is current as of August 2024.
Cohere aims to mitigate biases through diverse training datasets. However, continuous evaluation is necessary to ensure fairness and robustness in real-world applications.
The Command R+ model delivers strong performance across key metrics while maintaining a cost-effective pricing structure. In multilingual translation, Command R+ achieves a BLEU score of 35.9, closely rivaling GPT-4 Turbo’s 36.6 and significantly outperforming Mistral-Large at 31.4. For retrieval-augmented generation (RAG) tasks, it scores 71.5% accuracy, surpassing Mistral-Large (60.7%) and coming close to GPT-4 Turbo’s 76.7%. Additionally, in tool usage, Command R+ achieves a success rate of 74.5%, better than Mistral-Large’s 63.1% and nearly matching GPT-4 Turbo’s 73.7%.
The model is available on the AI/ML API platform as "cohere/command-r-plus" .
Detailed API Documentation is available here.
Cohere emphasizes data privacy and security in its model development. Ethical considerations include ensuring that the model does not propagate biases present in the training data.
Commercial usage rights are available through Cohere’s API services.
Get Command R+ API here.
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
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| Input | |
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| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| Intelligence | 5.3 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
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Command R+ This page | ||||
| Reasoning + agents | ||||
| Balanced coding + agents | ||||
| Long-context, multimodal & agentic workflows | ||||
| Reasoning + agents |
Yes, Command R+ can stream responses as they are generated.
Yes, Command R+ supports both function calling and structured outputs.
Command R+ was built by Cohere.
No. Its listed capabilities are function calling, streaming, and structured outputs, with no image or video input support mentioned.
Command R+ is accessed via the v1/chat/completions endpoint.
