Command - 2026 Pricing, Features, Reviews & Alternatives

Command is a family of large language models designed for enterprise text generation and AI workflow automation. The family spans multiple model variants, including general-purpose, reasoning, vision, and translation-specialized models, each optimized for distinct use cases such as retrieval augmented generation (RAG), agentic AI, copywriting, document analysis, and conversational applications. Models are accessible via a Chat endpoint that supports both standard and RAG-augmented inference, and integrate with external tools including search engines, APIs, functions, and vector databases through single-step and multi-step tool use.

Deployment options span the full spectrum of enterprise infrastructure requirements: a Cohere-managed SaaS API, dedicated single-tenant Model Vault inference with an encrypted confidential-computing tier, private VPC deployments on AWS EC2/EKS and other cloud environments, fully air-gapped on-premises installation, and third-party cloud AI services via Amazon Bedrock, Amazon SageMaker, Microsoft Azure AI Foundry, and Oracle Cloud Infrastructure Generative AI. Command A+ is additionally available as open-source weights under an Apache 2.0 license on Hugging Face in BF16, FP8, and W4A4 quantizations. This deployment breadth gives enterprises direct control over data residency, compliance posture, and vendor dependency.

Command serves enterprise organizations across Financial Services, Public Sector, Technology, Telecommunications, Energy and Utilities, Healthcare and Life Sciences, and Manufacturing. Key capabilities include multilingual generation across up to 48 languages (Command A+), multimodal text-and-image input for document analysis, chart interpretation, and OCR (Command A Vision and Command A+), a dedicated reasoning mode with configurable token budgets, configurable safety guardrails, structured outputs, and fine-tuning support for generative, classification, rerank, and chat tasks. Command A+ uses a sparse Mixture-of-Experts architecture with 218B total and 25B active parameters, enabling high-throughput, low-latency inference on as few as two H100 GPUs or a single B200 GPU.