Command A

Command A is an enterprise language model (LLM) developed by Cohere and released on March 13, 2025. The model was created specifically for business environments that require processing large volumes of information, integration with enterprise internal systems, and high task execution speed.

The main feature of Command A is its exceptional efficiency in using computing resources. The model can run on just two NVIDIA A100 or H100 GPUs, while many alternatives require up to 32 GPUs. This allows companies to significantly reduce infrastructure and energy costs.

At the same time, Command A maintains impressive specifications: a context of up to 256 thousand tokens and generation speeds of up to 156 tokens per second. This makes the model suitable for working with long documents, complex queries, and large corporate datasets.

Command A Specifications

Below are the key technical and functional specifications of the model:

Specification	Value
Type	Language model (LLM)
Developer	Cohere
Release date	March 13, 2025
Purpose	Enterprise use
Number of GPUs required	2 NVIDIA A100 or H100 GPUs
Performance	156 tokens per second
Maximum context length	256,000 tokens
Number of supported languages	23 languages
Supported languages	English, French, Spanish, German, Italian, Portuguese, Japanese, Korean, Arabic, Chinese, and others
Free tier	Yes (chatbot via web application)
Integration	Via API, available on Hugging Face

Who is Command A suitable for?

Enterprises and corporate users

Command A is primarily aimed at companies that need to process large volumes of text information: contracts, reports, correspondence, and technical documentation. The model handles these tasks faster and more cost-effectively than many alternatives.

Teams implementing RAG systems

Thanks to its optimization for Retrieval-Augmented Generation (RAG) tasks, Command A is suitable for organizations building question-answering systems with their own knowledge base: help desks, corporate assistants, and search portals.

Developers and integrators

For technical specialists, the model is interesting as a ready-made solution for integration via API. The ability to deploy the model with minimal hardware requirements lowers the entry barrier for companies without powerful server infrastructure.

How to use Command A?

Via web application

To get started, you need to register on the coral.cohere.com website and log in to your account. The interface allows you to select the desired operating mode: text generation, RAG mode, or API access. After that, you can upload data or enter queries and get results — this is the basic scenario available to all users.

Via API and Hugging Face

For enterprise use, integration via API is provided — this allows embedding the model into existing business systems and automating text processing workflows. Additionally, the model is published on the Hugging Face platform, which simplifies testing and adaptation to specific needs.

Key features of Command A

Working with text in 23 languages

The model understands and generates text in 23 languages, including English, German, French, Spanish, Japanese, Korean, Arabic, and Chinese. This makes it a versatile tool for international teams and global companies. Command A answers questions on a wide range of topics, performs translations, and creates unique texts based on specified parameters: topic, style, and tone.

Analytics and logical tasks

The neural network analyzes text sentiment, determines mood, and highlights key words. It can solve mathematical and logical problems, expanding its applications in analytics and data processing. Additionally, the model helps with writing essays, articles, and stories: it provides ideas and suggests corrections.

Integration and RAG

Command A is optimized for working with RAG systems, allowing it to be connected to corporate knowledge bases. The model integrates via API and can learn from new data, gradually improving its skills within a specific business context.

Advantages of Command A

Resource efficiency

The main advantage of the model is its ability to run on just two GPUs. This significantly reduces computing costs compared to competitors: many modern models at the level of GPT-4o require considerably more resources (up to 32 GPUs). For enterprises, this means lower costs for purchasing and maintaining equipment.

High performance

Command A delivers performance comparable to GPT-4o and DeepSeek with significantly lower hardware requirements. A context of up to 256 thousand tokens allows processing entire documents without losing meaning, and generation speeds reach 156 tokens per second.

Accessibility and language support

The company offers a free chatbot in the web application, allowing users to evaluate the model's capabilities without financial investment. Command A fully supports English and many other major languages.

Disadvantages of Command A

Detailed information about the model's disadvantages is not available in public sources. We can only note that, like any enterprise model, Command A may require a certain level of technical expertise during implementation, and the terms of paid plans have not been officially disclosed. The announced release date (March 2025) means the model is relatively new, and its integration ecosystem is still being formed.

What tasks does Command A solve?

Processing large contexts

Thanks to its 256-thousand-token window, the model can analyze long documents, contracts, scientific articles, and extensive reports in their entirety without splitting them into fragments. This preserves context and improves answer accuracy.

Text generation, analysis, and translation

Command A creates texts based on specified parameters, analyzes sentiment and key words, and performs translations between supported languages. This covers a wide range of enterprise tasks — from marketing materials to internal documentation.

Logic, mathematics, and RAG

The model solves mathematical and logical problems, which is useful for analytical departments. Full support for RAG tasks deserves special mention: integration with enterprise internal databases allows building accurate and up-to-date answers based on the company's own materials.

Command A pricing

The chatbot based on Command A is available for free through the web application at coral.cohere.com. All you need to do is register. The cost of paid plans and the terms of enterprise licenses are not disclosed on the official page — to obtain information about commercial terms, you need to contact Cohere representatives directly.

Terms of use for Command A

To work with Command A, registration on the coral.cohere.com website is required. After creating an account, users get access to the web interface, where they can select an operating mode (text, RAG, or API), upload their own data or enter a query, and get a result. The public version of the model is also available on the Hugging Face platform.

Availability of Command A

The model is available in three main ways: through the web application at coral.cohere.com, via API for enterprise integration, and through the Hugging Face platform for developers. Command A supports 23 languages and does not require installation on your own hardware — internet access and registration are sufficient.

How Command A differs from alternatives

Comparison with GPT-4o and DeepSeek

Command A directly competes with models such as GPT-4o and DeepSeek. The main difference is significantly lower computing costs: the model needs only two GPUs, while alternatives may require up to 32. At the same time, Command A's performance remains comparable to competitors, making it an attractive solution for companies with limited IT budgets.

Practical significance

For businesses, this means the ability to deploy a powerful language model without significant investment in server infrastructure. Lower energy and equipment consumption reduces both capital and operational expenses, which is especially important for mid-sized companies and startups integrating AI solutions into their products.

Conclusion

Command A is an enterprise language model from Cohere, optimized for efficient operation on two GPUs with a context of up to 256 thousand tokens and support for 23 languages. It combines high performance with computing resource efficiency, offers free web access, and provides open integration via API and Hugging Face. The model is suitable for enterprises that need large-scale data processing, RAG system integration, and text generation in multiple languages.