AI model by Cohere
Cohere Command A+ for business
Cohere's enterprise flagship for multimodal, multilingual agent tasks, with 48 languages, tool calling, JSON output and open weights under Apache 2.0.
- General purpose
- Open weights
- Vision and multimodal
- Open weights
- Reviewed on September 24, 2026
- Cohere
Capability tiersRelative, not benchmarks
Key facts about Cohere Command A+
- Model ID at review
- command-a-plus-05-2026
- Provider
- Cohere
- Main category
- General purpose
- Open weights
- Yes, Apache 2.0
- Last reviewed
- September 24, 2026
Fit
Where it fits and where it does not
Good at
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Enterprise agent tasks with tools.
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Many languages, 48 at review time.
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Image input with text.
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Running on modest hardware for its class.
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Open weights under Apache 2.0.
Not the right choice for
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Inputs over its 128K token window.
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Audio or video input.
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The hardest reasoning tasks, where top models lead.
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Adoption without testing, since it is recent.
Use cases
Business use cases we would use it for
Multilingual support
Enterprise search assistants
Private deployment
Our notes
When we would choose it
Command A+ was released by Cohere in May 2026 and is now its flagship. Cohere positions it for complex multimodal, multilingual agentic enterprise tasks on minimal hardware. It supports 48 languages, image input, tool calling and JSON output, with a 128K token input window and up to 64K output tokens. It is a mixture-of-experts model, and an open-weight version is published under Apache 2.0.
Cohere's focus has always been enterprise use: search, retrieval and assistants for business data. Command A+ fits naturally with Cohere Embed and Cohere Rerank in a knowledge assistant built on one provider.
The open weights make it one of the few enterprise-focused models you can run in your own environment. For companies with strict data rules, that is a real advantage.
The older Command A from 2025 is still live, with a 256K window but text only. Cohere also lists specialized versions for reasoning, vision and translation. We did not verify pricing at review time, so the price level here is an estimate.
We would include Command A+ in a comparison when languages beyond English matter, or when open weights and enterprise support are both needed. See RAG knowledge assistants.
Before you commit
Things to check before you commit
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Context
The input window is 128K tokens with up to 64K output.
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Pricing
We did not verify API pricing at review time.
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Self-hosting
Check the hardware needs of the published open-weight version.
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Older models
Command A from 2025 is still live. Compare both.
Alternatives
Models to compare it with
Cohere Embed v4
Cohere's multimodal embedding model for enterprise search, embedding text, images and mixed documents, with flexible vector sizes and long inputs.
Cohere Rerank 4
Cohere's multilingual rerank models, which sort search results by relevance, in a best-quality Pro version and a low-latency Fast version.
Mistral Large 3
Mistral's open-weight general-purpose flagship under Apache 2.0, with image input, tool calling, structured outputs and a 256K token window.
Keep exploring
Solutions, services and guides
Related services
View all related services- RAG knowledge assistants Assistants that answer questions from your own documents and show where each answer came from.
- LLM integration Add a large language model to software you already have, with the guardrails, costs and logging handled.
- AI Product Development AI agents, knowledge assistants, copilots and document automation built into the way your team already works.
- AI copilots AI helpers built into your product or internal tools that draft, summarize and suggest while people decide.
- AI chatbots Website and messaging chatbots that answer common questions well and hand everything else to a person.
Solutions
View all solutions- Knowledge assistant (RAG) Ask a question in plain words and get an answer from your own documents, with links to the sources.
- AI translation workflows Translate websites, products and support content quickly with AI, a shared glossary and native-speaker review where it matters.
- AI-assisted content workflows Briefs, first drafts, edits and repurposing in a workflow where people set the angle and approve every word.
- AI support agent An assistant that answers routine questions from your own content, checks orders and hands anything else to a person.
- Automated quoting Draft accurate quotes and proposals from a request, your price rules and past work, for a person to approve.
- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
Industries
View all industries- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Education and elearning Course platforms, student portals, content workflows and AI tutoring assistants for schools and training companies.
- Healthcare Patient booking, intake forms, internal knowledge assistants and admin automation for clinics and care providers.
- Professional services Client portals, proposal drafting, knowledge assistants and internal tools for consultancies, agencies and firms.
Case studies
View all case studiesGuides and articles
View all guides and articles- What is RAG and when do you need it? How retrieval-augmented generation lets AI answer from your documents, when it fits and how to build it well.
- RAG vs fine-tuning Two ways to make AI work with your knowledge, compared by cost, accuracy and upkeep.
- How to choose an AI model for your business A step-by-step way to pick an AI model by testing candidates on your own tasks, data rules and budget.
- How to keep customer data safe when using AI Practical steps to protect customer data when you use AI services, from data terms to access and logging.
MCP servers
View all mcp servers- Box Box's official MCP server lets AI search and read files, ask questions across documents with Box AI, extract data and upload files.
- Confluence Atlassian's official Rovo MCP server lets AI search and read Confluence spaces and pages, create and edit content and add comments and labels.
- Google Drive Google's own Drive MCP server lets AI search, read and create files in Google Drive, with your Google Workspace sign-in.
- Memory The MCP project's Memory reference server gives AI a local knowledge graph to store people, things and facts and recall them later.
- Obsidian A community MCP server that lets AI list, read, search, edit, append to and delete notes in an Obsidian vault through the Local REST API plugin.
- Readwise Readwise's official hosted MCP server lets AI search and manage your reading highlights and Reader documents.
Glossary terms
View all glossary terms- RAG RAG, or retrieval-augmented generation, is a method where an AI system first finds relevant passages in your documents, then answers using only those passages.
- Large language model A large language model, or LLM, is an AI model trained on vast amounts of text that can understand and generate language, and often images and code.
- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- Hallucination A hallucination is when an AI model states something false or invented as if it were true, such as a made-up fact, figure or source.
- Chatbot A chatbot is software that holds a conversation with people through text or voice, answering questions or completing simple tasks.
- Context window A context window is the maximum amount of text, measured in tokens, that an AI model can consider at once, including the question, documents and its answer.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
Cohere lists 48 languages.
An open-weight version is published under Apache 2.0.
128K tokens of input and up to 64K output tokens.