Curiosity · AI Model
Command R
Command R, launched by Cohere in March 2024, is the first member of the Command R-series. It targets enterprise retrieval-augmented generation: grounded responses that cite the underlying documents, native tool use, and strong multilingual coverage across 10+ business-critical languages. A 128K context window and permissive per-token pricing made it a popular RAG default.
Model specs
- Vendor
- Cohere
- Family
- Command R
- Released
- 2024-03
- Context window
- 128,000 tokens
- Modalities
- text
- Input price
- $0.5/M tok
- Output price
- $1.5/M tok
- Pricing as of
- 2026-04-20
Strengths
- Strong grounding and citation quality in RAG workflows
- Native tool use and JSON mode
- Broad multilingual coverage out of the box
Limitations
- Raw reasoning below frontier Claude/GPT/Gemini tiers
- No vision or audio modalities
- Smaller developer ecosystem than OpenAI/Anthropic
Use cases
- Enterprise RAG over internal knowledge bases
- Multilingual customer-support chatbots
- Tool-using agents on structured business data
- Grounded question-answering with citations
Benchmarks
| Benchmark | Score | As of |
|---|---|---|
| RAG QA (Cohere internal) | state-of-the-art for its class at launch | 2024-03 |
| MMLU | ≈68% | 2024-03 |
Frequently asked questions
What is Command R?
Command R is Cohere's mid-size production LLM, released in March 2024 and optimised for retrieval-augmented generation, multilingual chat, and tool use in enterprise settings.
What makes Command R a RAG-first model?
Cohere trained Command R to cite the supporting documents for its answers, to follow structured tool-use patterns, and to handle long 128K-token contexts — all priorities for enterprise RAG pipelines.
How does Command R compare to Command R+?
Command R+ is the larger, higher-quality sibling. Command R is cheaper and fast; R+ has stronger reasoning and is preferred for harder RAG and agent workflows.
Sources
- Cohere — Command R launch — accessed 2026-04-20
- Cohere — Pricing — accessed 2026-04-20