Cohere: Command R+ (08-2024)

Command R+ (08-2024) is a text generation model from Cohere, released by the provider on 30 August 2024. It is an update to the earlier Command R+ model, and Cohere describes it as delivering roughly 50 percent higher throughput and 25 percent lower latencies than the previous version, while keeping the same hardware footprint. If you have used Command R+ before, this is the newer checkpoint of that same line rather than a different family of model.

The model works with text in and text out. It accepts up to 128,000 tokens of context, which is enough to fit long documents, transcripts or multi turn conversations in a single request. Output is capped at 4,000 tokens per response, so it is suited to answers, summaries and structured payloads rather than very long generated documents. Its knowledge cutoff is 31 March 2024, meaning anything after that date has to come from the prompt, from tools, or from retrieval. The supported parameters include temperature, top_p, top_k, frequency_penalty, presence_penalty, max_tokens, stop, seed and response_format, plus tools, tool_choice and structured_outputs for tool calling and constrained generation.

That feature set points to a few practical patterns. Retrieval augmented generation is a natural fit: the long context lets you paste retrieved passages alongside the question. Tool calling and structured outputs make it usable as the reasoning step in an agent, where the model decides which function to call and returns arguments in a schema you define. Because both tools and response_format are supported, you can build pipelines that mix free text answers with machine readable JSON. The 128,000 token window also helps for summarising long reports, extracting fields from contracts, or answering questions over a codebase or documentation set in one pass.

Through api14 you call it with the OpenAI compatible chat completions endpoint and the model id "cohere/command-r-plus-08-2024". Requests use the familiar messages format, so existing OpenAI SDK clients work after pointing the base URL at api14 and swapping the model name. The request body can carry any of the supported parameters: temperature, top_p, top_k, frequency_penalty, presence_penalty, max_tokens, stop, seed, response_format, tools, tool_choice and structured_outputs. Note that max_tokens governs the generated reply and cannot exceed the 4,000 token output cap, even though the context window is much larger.

Two constraints are worth planning around. The 4,000 token output limit means long form generation, such as entire chapters or large code files in one response, may need chunking or a model with a higher output ceiling. The March 2024 knowledge cutoff also means time sensitive questions depend on what you supply in the prompt or through tools. If your workload is mostly images or audio, this model is not the fit, since it only handles text. For straightforward text tasks within those bounds, it is a reasonable default.