What is Command A Translate?
Command A Translate is a specialized language model from Cohere for machine translation. Its primary task is converting text from one supported language into another while preserving meaning and producing fluent output. The model has 111 billion parameters and is available through Cohere’s Chat API under the model ID command-a-translate-08-2025.
Unlike a general conversational model, Command A Translate is positioned specifically around translation quality and multilingual workflows. That makes it a practical fit for business documents, multilingual communications, enterprise knowledge, and other text where consistent language handling matters more than broad creative or reasoning features.
Cohere released the model on August 28, 2025. In Cohere’s current lineup, it belongs to the Command family, but it has a narrower role than a general-purpose Command model: it is intended primarily for translation rather than open-ended assistance.
Specifications and supported languages
The following are the main verified specifications supplied for the model:
| Specification | Details |
|---|---|
| Provider | Cohere |
| Model ID | command-a-translate-08-2025 |
| Release date | August 28, 2025 |
| Parameters | 111 billion |
| Context listing | 8,000 tokens in Cohere’s model catalog |
| Maximum input | 8,000 tokens in the detailed model documentation |
| Maximum output | 8,000 tokens |
| Input | Text |
| Output | Text |
| API | Cohere Chat API |
| Knowledge cutoff | June 1, 2024 |
There is a documentation distinction worth noting. Cohere’s model catalog lists an 8,000-token context window, while the detailed description explains the working budget as up to 8,000 input tokens plus up to 8,000 output tokens. For implementation planning, the separate input and output limits are the more useful interpretation, but developers should verify the active limit in the API documentation and their account configuration.
Command A Translate supports 23 languages: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Chinese, Arabic, Russian, Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian, Romanian, Greek, Hindi, Hebrew, and Persian. The supplied documentation does not provide a separate quality ranking for individual language pairs, so the model should be evaluated with representative business text before deployment.
Translation capabilities and modalities
The model accepts text and produces text. It does not natively process images, audio, or video, and it does not generate non-text media. A document containing scanned pages, speech, or visual layouts would therefore need to be converted into usable text by another system before Command A Translate can translate it.
Its intended workflow can be simple: an application sends source text, identifies the desired translation task through the prompt or request, and receives translated text. It can also be incorporated into longer enterprise translation pipelines for documents, internal communications, or multilingual knowledge bases. Longer source material may need to be divided into sections because the documented input limit is 8,000 tokens.
Cohere’s documentation displays capabilities associated with multilingual tasks, citations, tool use, structured outputs, and reasoning. However, these features should not be confused with the model’s main purpose. Command A Translate is primarily a translation model. The supplied research does not establish a specialized coding capability, a distinct reasoning benchmark, or a general-purpose agent profile for this model.
Enterprise deployment and privacy considerations
A notable reason to consider Command A Translate is its availability through private deployment options for enterprise customers. Cohere states that the model is optimized to run on one or two A100 or H100 GPUs. This can be relevant to organizations translating sensitive documents, regulated information, or internal knowledge that should remain within controlled infrastructure.
Private deployment does not automatically make every implementation compliant with a particular regulation. Organizations still need to review the selected deployment architecture, retention settings, access controls, contractual terms, and data-processing arrangements. The practical advantage is deployment control: some customers may be able to keep translation workloads in infrastructure managed according to their own security and governance requirements.
For teams that do not need private hosting, the Cohere Chat API provides the simpler integration path. API usage is still subject to account, rate-limit, and production-access conditions.
Pricing and API access
Cohere’s documentation states that Command A Translate is free for trial and production keys until applicable rate limits are reached. This is not the same as unlimited free usage. The documented trial limit is 20 requests per minute, while production limits are provided through Cohere’s sales process.
Production use requires contacting Cohere’s sales team. The supplied research does not provide a recurring per-token price or a fixed public production tariff, so there is no verified numeric input or output price to report. Organizations should treat the model as rate-limited and sales-managed rather than assuming that the trial arrangement will cover unrestricted commercial traffic.
The model is accessed through Cohere’s Chat API using command-a-translate-08-2025. Developers should confirm current authentication, request-format, rate-limit, and production-approval requirements in Cohere’s documentation before building a production integration.
Strengths and limitations
Where Command A Translate is strong
- Translation focus: It is purpose-built for machine translation instead of being a general chatbot adapted to translation tasks.
- Broad language coverage: Its 23 supported languages cover major European, Asian, and Middle Eastern languages.
- Longer text handling: The documented 8,000-token input and 8,000-token output limits can accommodate more substantial passages than a short sentence-by-sentence workflow.
- Enterprise deployment: Private deployment options can help organizations with sensitive translation data and infrastructure-control requirements.
- API integration: The Chat API makes it suitable for embedding translation into document, communication, or knowledge-management systems.
Important limitations
- Text only: It cannot directly translate images, audio, or video without a separate extraction or transcription stage.
- Narrower purpose: It is not presented as Cohere’s primary model for general reasoning, coding, or vision tasks.
- Production availability: Production access is subject to rate limits and a sales-managed process.
- Knowledge cutoff: Its underlying knowledge cutoff is June 1, 2024. This is less important for direct translation than for factual rewriting or requests that require current world knowledge, but current context should be supplied explicitly when needed.
- Deployment requirements: Private hosting may provide greater control, but it also introduces infrastructure, integration, and operational responsibilities.
Speed, cost, and capability trade-offs
The supplied research rates the model highly for speed and cost relative to the other models in the available evaluation data, but those are editorial scores rather than Cohere-published benchmark results. They should be treated as comparative guidance, not guaranteed latency or price measurements.
In practical terms, Command A Translate offers a focused alternative to using a broad general-purpose model for every translation request. A specialized translation model may simplify the task and avoid paying for capabilities that a translation pipeline does not need. However, the lack of a published production price means the real cost advantage must be confirmed with Cohere for the expected request volume.
Latency will also depend on request length, deployment choice, traffic, rate limits, and whether the application processes documents sequentially or in parallel. The research supports describing the model as suitable for high-throughput enterprise workflows, but it does not establish a universal response-time guarantee.
When to choose Command A Translate
Command A Translate is a strong candidate when the central requirement is multilingual text translation and the organization values enterprise deployment options. Suitable examples include:
- Translating internal business documents between supported languages.
- Localizing multilingual communications or knowledge-base content.
- Building an enterprise translation service behind an API.
- Processing sensitive text through a private deployment.
- Handling longer source passages within the documented token limits.
It is less appropriate when the workflow begins with images, recordings, or video, because those inputs require other models or preprocessing tools. A general-purpose model may also be a better fit when the same request must combine translation with extensive reasoning, software generation, visual analysis, or broad conversational assistance.
Teams should also compare the model with other translation systems using their own language pairs and content. Legal, technical, medical, and customer-facing text can have different terminology and error tolerances. A small pilot should measure terminology consistency, formatting preservation, review effort, and performance at the intended document length before full deployment.
Overall assessment
Command A Translate is best understood as a focused enterprise translation model, not as an all-purpose AI assistant. Its defining characteristics are 23-language coverage, text-only input and output, an 8,000-token input and output budget, Chat API access, and private deployment options. Those characteristics make it relevant to organizations that need integrated multilingual workflows with more control over data and infrastructure.
Its main trade-off is scope. The model’s specialization is useful when translation is the primary job, but it does not replace a vision, audio, coding, or general reasoning model. Pricing beyond the rate-limited free access arrangement is not publicly specified in the supplied research, so commercial buyers should confirm terms and limits with Cohere before selecting it for production.