Cohere offers a powerful lineup of generative models tailored to excel in real-world enterprise scenarios, retrieval-augmented generation (RAG), and contextual understanding. Its flagship models, such as Command R+, Command R, and Embed 3, are designed for scalable, efficient performance in conversational AI and semantic search. By combining contextual insights with enhanced generative capabilities, Cohere enables developers to build applications that handle multi-turn dialogues, long-context tasks, and advanced search queries.

Cohere Models and Pricing:

Command R+:

• Description: Cohere’s most powerful large language model (LLM) optimized for real-world enterprise applications.
• Input Cost: $2.50 per 1M tokens.
• Output Cost: $10.00 per 1M tokens.
• Use Cases: Enterprise-grade AI applications requiring high performance and scalability.

Command R:

• Description: A model designed for long-context tasks such as RAG and API integration.
  • Standard Version:
    • Input Cost: $0.15 per 1M tokens.
    • Output Cost: $0.60 per 1M tokens.
  • Fine-Tuned Version:
    • Input Cost: $0.30 per 1M tokens.
    • Output Cost: $1.20 per 1M tokens.
    • Training Cost: $3.00 per 1M tokens.
• Use Cases: Applications requiring in-depth context handling and integration with external tools.

Rerank 3:

• Description: Boosts search quality for keyword or vector search systems, enhancing relevance without replacing the existing infrastructure.
• Cost: $2.00 per 1K searches.
• Use Cases: Semantic search and retrieval systems.

Embed 3:

• Description: A multimodal embedding model that acts as an intelligent engine for RAG systems and semantic search.
• Text Cost: $0.10 per 1M tokens.
• Image Cost: $0.0001 per image.
• Use Cases: Semantic embedding for text and image retrieval.