frontierreasoning

Cohere

Enterprise-grade NLP models optimised for RAG, semantic search, and private deployment.

3
Models tracked
2019
Founded
Command A
Flagship model
Toronto
HQ

About

About Cohere

Cohere focuses on enterprise NLP — particularly retrieval-augmented generation (RAG), semantic search, and text classification. Founded in 2019 by former Google Brain researchers, Cohere's Command models are optimised for business document processing, while their Embed models power production-grade vector search. Cohere offers both cloud API access and private deployment for air-gapped environments.

Key highlights

  • Purpose-built for enterprise RAG, semantic search, and NLP pipelines

  • Native citation grounding in Command R models for verifiable answers

  • Private cloud and on-premise deployment options for regulated industries

  • Embed 3 leads semantic search benchmarks (MTEB leaderboard)

  • Specialised focus on business document processing and extraction

Models

3 models tracked

Context windows, pricing, capabilities, and API identifiers — everything you need to choose the right model for your workload.

Flagship

Command A

2025

256Kcontext
TextCodeReasoning

Cohere's most capable model with a 256K context window. Designed for complex multi-step agentic tasks, enterprise document processing, and production RAG pipelines.

  • 256K context
  • Enterprise agentic tasks
  • Complex tool use
  • Multi-step reasoning
In: $2.50 / M tokens
Out: $10 / M tokens
command-a-03-2025

Command R+

2024

128Kcontext
TextCode

Optimised for retrieval-augmented generation with native citation grounding. Returns answers with source citations from retrieved documents — ideal for enterprise knowledge bases.

  • RAG-optimised
  • Native citation grounding
  • Multilingual (10 languages)
  • Tool use
In: $2.50 / M tokens
Out: $10 / M tokens
command-r-plus

Embed 3 English

2023

512 tokenscontext
Embed

State-of-the-art text embedding model for semantic search and RAG pipelines. Leads MTEB benchmarks and supports both text and image embeddings.

  • Top MTEB benchmark
  • Vector store optimised
  • Image + text embeddings
  • High recall
In: $0.10 / M tokens
embed-english-v3.0

Use Cases

What Cohere is best for

Each provider has specialisms shaped by their architecture decisions, training data, and API design. Here is where Cohere performs best.

Enterprise knowledge bases
Semantic search platforms
Document classification at scale
Private on-premise AI
Multilingual customer intelligence

Get started

Start building with Cohere

Visit the official Cohere platform to access API keys, documentation, and pricing details.