Command A is Cohere’s most powerful enterprise LLM for real business tasks such as tool use, retrieval-augmented generation, agents, and multilingual workflows.
The model has 111 billion parameters, supports 23 languages, features a 256k context window, and according to Cohere is designed for a comparatively low inference footprint.
Command A
LLM “Our largest, most performant model, ideal for building enterprise agents with a low compute footprint.” - “Max performance, minimal compute”
Location: Canada ⓘ Cohere Inc., 171 John Street, Suite 200, Toronto, Ontario M5T 1X3, Canada.
Enterprise / Private Deployment VPC, on-premises, or air-gapped deployment for companies with strict data protection, security, and data residency requirements.
North / Compass / Embed / Rerank Complementary Cohere products for agents, enterprise search, embeddings, and retrieval
Target Audience
Command A is aimed primarily at companies, developer teams, AI product teams, IT architects, regulated industries, SaaS providers, banks, insurance companies, public authorities, healthcare-related organizations, and large knowledge organizations. The model is intended less as a consumer chatbot and more as an enterprise building block for production AI systems that need to access company data, tools, APIs, vector databases, and internal knowledge sources. In its documentation, Cohere emphasizes Tool Use, RAG, agents, and multilingual business applications in particular as core strengths.
Outstanding Features
Outstanding features include the 256k context window, the focus on Retrieval-Augmented Generation, Tool Use, agent workflows, structured outputs, citations/grounding, and multilingual applications in 23 languages. Command A can be connected to external tools such as APIs, search engines, databases, and vector databases, making it suitable for realistic enterprise processes, not just isolated chat responses. Cohere also highlights that Command A requires only two A100/H100 GPUs to operate, which can make it more attractive for private or on-premise deployments than significantly larger models.
Most Important Use Cases
The most important use cases are internal knowledge assistants, RAG systems, enterprise search, customer service automation, agents with tool access, API orchestration, document QA, financial/reporting analysis, multilingual communication, translation, code/SQL generation, process automation, and research agents. In the technical report, Cohere explicitly describes Command A as a model for real enterprise settings, including RAG, Tool Use, agentic workflows, multilingual tasks, and code/SQL-related enterprise scenarios.
Usage & Notes
Command A can be used via Cohere’s API, including Chat V2, Chat V1, and Chat Completions; Cohere also provides an OpenAI-compatible API to make it easier to switch existing OpenAI SDK integrations to Cohere. For production use, companies should decide early on whether they want to use the public Cohere Platform, a cloud AI service such as AWS/Azure/OCI, a private cloud/VPC, Model Vault, or on-premises. For GDPR-sensitive data, it is especially important to document in advance the training opt-out, DPA/AVV, subprocessors, region, data retention, logging, tool integrations, and possible third-country transfers.
| Target Audience | Assessment |
|---|---|
| Developers / AI teams | Highly suitable – for LLM applications, RAG, Tool Use, agents, and multilingual enterprise workflows. |
| Large enterprises | Highly suitable – especially because of private deployment, VPC, and on-premises options. |
| Regulated industries | Highly suitable – if private deployment, data control, and own infrastructure are important. |
| SaaS / product teams | Suitable – for API-based AI features with Cohere models. |
| Private individuals | Rather unsuitable – Command A is primarily an enterprise/API model, not an end-user chatbot. |
Command A
Enterprise chat, RAG, Tool Use, agents, long contexts, multilingual business workflows, SQL/code-related tasks. Cohere states 111B parameters, 256k context, and a focus on Tool Use, RAG, agents, and multilinguality.
Command A Reasoning
Complex problem-solving, agentic workflows, multi-step reasoning, Tool Use, RAG, demanding enterprise tasks. Cohere states 111B parameters, 256k context, and up to 32k output tokens.
Command A Vision
Image and document understanding, charts, tables, OCR, visual analysis, document QA, multilingual image/text tasks. Cohere states 128k context and up to 20 images per request.
Command A Translate
Professional translation, multilingual business communication, localization, cross-lingual workflows. Cohere lists Command A Translate as part of the Command model family.
Hosting & Data
1) On-prem / local hosting
Meaning: The company operates the solution on its own hardware or within its own infrastructure. In the strictest sense, not only the application runs locally, but ideally the model as well.
2) Private cloud / data center
Meaning: The solution runs in a dedicated or more clearly separated cloud environment, often with a hosting provider or hyperscaler, but in a German data center or in a particularly controlled environment.
3) EU SaaS / managed
Meaning: The provider operates the solution itself as a service. The company uses the tool as a ready-made cloud service, ideally with EU data residency.
4) Hybrid
Meaning: One part of the processing remains internal / local / in a private cloud, while another part runs in an external cloud or EU SaaS.
5) AVV / DPA
Meaning: This is the data processing agreement or Data Processing Addendum. It governs that the provider processes personal data on behalf of the customer and is bound by the customer's instructions.
6) No training
Meaning: The provider does not use your prompts, uploads, attachments, chat histories, or outputs for training or improving the general model — ideally excluded by contract.
7) Open-source / transparency path
Meaning: There is a path toward greater technical transparency and sovereignty, for example through:
- open models
- documented components
- self-hostable parts
- traceable architecture
- export / switching options
| On-prem / local hosting | ✅ |
| Private cloud / data center | ✅ |
| EU SaaS / Managed | ⚠️ |
| Hybrid | ✅ |
| DPA / AVV | ✅ |
| No training on customer data | ✅ |
| Open source / transparency path | ⚠️ |
Overall assessment of hosting & data:
Command A is an enterprise LLM for tool use, RAG, agents, and multilingual tasks. Cohere offers managed API, private cloud/VPC, and on-premises deployments; according to the documentation, private deployments can also run in air-gapped environments. Positives include 256k context, enterprise focus, private deployment, RAG/agent strength, and reduced data leakage risks with on-prem/VPC. A critical point is that self-/private hosting requires technical infrastructure and an enterprise contract.
Conclusion:
Command A is particularly strong for companies that want to integrate LLMs into their own systems in a controlled way while retaining data sovereignty.
| On-prem / local hosting | ✅ |
| Private cloud / data center | ✅ |
| EU SaaS / Managed | ⚠️ |
| Hybrid | ✅ |
| DPA / AVV | ✅ |
| No training on customer data | ✅ |
| Open source / transparency path | ⚠️ |
Overall assessment of hosting & data:
Command A is an enterprise LLM for tool use, RAG, agents, and multilingual tasks. Cohere offers managed API, private cloud/VPC, and on-premises deployments; according to the documentation, private deployments can also run in air-gapped environments. Positives include 256k context, enterprise focus, private deployment, RAG/agent strength, and reduced data leakage risks with on-prem/VPC. A critical point is that self-/private hosting requires technical infrastructure and an enterprise contract.
Conclusion:
Command A is particularly strong for companies that want to integrate LLMs into their own systems in a controlled way while retaining data sovereignty.
Strengths & weaknesses at a glance
| Strengths | Weaknesses |
|---|---|
| • Very strong for RAG, tool use, agents, and enterprise automation. | • Command A is primarily a text model; Command A Vision is provided separately for image input. |
| • 256k context window for long documents and large knowledge contexts. | • The research weights are CC-BY-NC, so they are not freely available for commercial use. |
| • Supports 23 business languages, including German, English, French, Spanish, Italian, Portuguese, Japanese, Korean, Chinese, and Arabic. | • According to the Trust Center, Cohere SaaS runs on Google Cloud in US-Central; EU-only SaaS is not documented for the public Cohere platform. |
| • Comparatively efficient operation: Cohere cites two A100/H100 GPUs as the hardware requirement. | • According to the Trust Center, a request or NDA is required for a DPA/AVV. |
| • Flexible deployment options: Cohere Platform, Cloud AI Services, Private Cloud/VPC, and on-premises. | • For productive use of newer variants such as Command A Reasoning, additional sales clarifications may be necessary. |
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GDPR-compliant usage possible?
GDPR assessment: Command A or Cohere is conditionally to well suited from a GDPR perspective, especially with an enterprise contract, DPA, and private deployment.
Positive is that Cohere documents enterprise data controls, DPA requests, security programs, and private deployments for VPC and on-premises. The hosting flexibility is particularly strong: Cohere can be operated in the customer's own private cloud or on-premises, allowing data residency and governance to be controlled more effectively.
Negative is that for public SaaS/API usage, specific server locations and training/data controls depend on the contract and deployment model; for enterprise usage, the DPA, training opt-out, retention, subprocessors, and region should be contractually reviewed.
Server location: For private deployment, freely selectable or controllable by the customer; for Cohere Managed Cloud, EU-only hosting cannot be generally guaranteed without a specific contract review. Further link: Cohere Privacy, Security, and Private Deployments.