Cohere's Command A Translate is a 111 billion parameter, open-source chat model that achieves state-of-the-art performance on translation quality, with capabilities including function calling, JSON mode, reasoning, streaming, and text generation. It is particularly suited for tasks that require long-range contextual understanding, thanks to its context window of 8,992 tokens and optimized transformer architecture with sliding window attention and relative positional encoding.
Input
Output
Context
9K
Max Output
8K
Parameters
111.1B
Input Modalities
Output Modalities
Loading capabilities…
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
The creator's other models in the catalog, with their context, size and license where published.
Put this model beside its alternatives on the same evidence, or go back to the full catalog.
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Command A Translate advertises a context window of 8,992 tokens, with a maximum output of 8,000 tokens in a single response. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
Yes. Command A Translate is an open-weight model released under the Cc by nc 4.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Command A Translate accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Command A Translate is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Command A Translate is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 109.9 GB at INT8 for the weights and a default context, from the catalog's 111.1B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Nov 4, 2026
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