About Cohere
Cohere is a Canadian AI company founded in 2019 by former Google Brain researchers, including Aidan Gomez—one of the co-authors of the original “Attention Is All You Need” Transformer paper. Based in Toronto, Cohere focuses on enterprise AI with a strong emphasis on retrieval-augmented generation (RAG) and multilingual capabilities.
The Command model family is designed specifically for enterprise use cases: tool use, document processing, and multi-step agentic workflows. Command A (2025) represents Cohere’s latest generation, offering GPT-4-tier performance at significantly lower computational cost with a 111B parameter MoE architecture.
Command Model Timeline
The evolution of Cohere’s Command family. Verified scores from the Command A Technical Report.
Command A
Cohere’s most capable model. Command A achieves 85.5% on MMLU, 50.8% on GPQA, and 90.9% on IFEval. A 111B parameter MoE architecture delivers strong performance with efficient inference, purpose-built for enterprise RAG and agentic workflows.
Command R+
The first model to bring Cohere into frontier territory. Command R+ achieved 88.2% on MMLU and introduced advanced multi-step tool use and strong RAG grounding, establishing Cohere as a serious enterprise AI contender.
Command R
An efficiency-focused model designed for production RAG workflows. Command R offered strong retrieval-augmented generation at lower latency and cost, making it popular for enterprise search and document analysis applications.
Benchmark Performance
Command A scores across verified benchmark categories.
Key Strengths
Command A achieves 90.9% on IFEval, one of the highest instruction-following scores across all providers—critical for enterprise applications where precise adherence to complex instructions matters.
Cohere models are purpose-built for retrieval-augmented generation, with native grounding, citation generation, and multi-step tool use designed for real-world enterprise document workflows.
Co-founded by Aidan Gomez, co-author of “Attention Is All You Need,” Cohere brings deep architectural expertise to model design, with a focus on practical deployment efficiency.
About This Data
Benchmark scores are sourced from Cohere’s official Command A Technical Report. Command R+ MMLU score is from Cohere’s model card. Note that Command A reports GPQA (not specifically GPQA Diamond); scores may not be directly comparable to providers that report the Diamond subset.
Explore More Providers
Compare Cohere’s Command models against other frontier AI systems.