Command
Enterprise models for RAG and business search.
Olya's profile
- What sets it apart
- Command is Cohere's model family, from a company that deliberately skipped the consumer race: no ChatGPT-style app, just models you embed in your own systems. The flagship Command A carries a 256K-token context and runs on just two GPUs (A100 or H100), a design aimed at teams that want to keep data in-house. Some recent versions like Command A+ (May 2026) ship under an Apache 2.0 license, so self-hosting is real rather than a slogan.
- Strengths
- It is built around retrieval from enterprise sources (RAG), reliable tool use, and the multi-step chains that agents need. It covers 23 languages and produces structured output predictably, which matters when the AI feeds a workflow rather than just chatting. On-premise or private-VPC deployment is arguably its strongest argument for anyone in a regulated sector.
- When to use it
- It fits when you are building internal search, assistants over corporate documentation, or agents that pull from databases and APIs while keeping control of where the data runs. It is a sensible pick for multilingual settings and for environments where compliance or data sovereignty weighs more than the trend of the moment.
- When to avoid it
- If you want a ready-made public-facing chatbot, this isn't it: Command is meant to be integrated, not opened and used. For frontier reasoning or heavy coding the large generalist models are often still ahead, and the pricing isn't cheap (Command A runs about $10 per million output tokens, while the top variants are 'contact sales').