> This page is for version v1 API. > For other versions, use one of these documentation indexes: > - v2 API (default): https://docs.cohere.com/v2/llms.txt > - v1 API: https://docs.cohere.com/v1/llms.txt > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.cohere.com/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.cohere.com/_mcp/server. # Using Cohere Models on OpenRouter > Use Cohere's Command, Embed, Rerank, and North models through OpenRouter, including the newly added Embed 5 and Rerank 5 models. Cohere models are supported on [OpenRouter](https://openrouter.ai), which provides a single API for models from many providers. You can use Cohere's Command, Embed, Rerank, and North models through OpenRouter with an OpenRouter API key. Browse them on [Cohere's OpenRouter page](https://openrouter.ai/cohere). ## Benefits * **One API and API key**: Use Cohere models alongside models from other providers, with one API key and one account for billing. * **Easy switching**: Move between models by changing the `model` parameter, without changing your integration. * **Served by Cohere**: Cohere is the provider for its models on OpenRouter, so OpenRouter forwards your requests to the Cohere API. ## Latest additions: Embed 5 and Rerank 5 The latest Cohere models on OpenRouter are Embed 5 and Rerank 5, each available in Pro and Fast variants: * **Embed 5** (`cohere/embed-5-pro`, `cohere/embed-5-fast`): Embeds text, images, and mixed text-and-image inputs such as PDF pages, with a 128k-token context window. Pro and Fast share an embedding space, so you can index with Pro and query with Fast. * **Rerank 5** (`cohere/rerank-5-pro`, `cohere/rerank-5-fast`): Reranks text with calibrated relevance scores, with a 32,768-token context window for each query and document combined. ## Available models | Model | OpenRouter model ID | Cohere API model ID | | --------------------------------------------------------------------------- | ------------------------------- | ------------------------ | | [Embed 5 Pro](https://openrouter.ai/cohere/embed-5-pro) | `cohere/embed-5-pro` | `embed-v5.0-pro` | | [Embed 5 Fast](https://openrouter.ai/cohere/embed-5-fast) | `cohere/embed-5-fast` | `embed-v5.0-fast` | | [Rerank 5 Pro](https://openrouter.ai/cohere/rerank-5-pro) | `cohere/rerank-5-pro` | `rerank-v5.0-pro` | | [Rerank 5 Fast](https://openrouter.ai/cohere/rerank-5-fast) | `cohere/rerank-5-fast` | `rerank-v5.0-fast` | | [Rerank 4 Pro](https://openrouter.ai/cohere/rerank-4-pro) | `cohere/rerank-4-pro` | `rerank-v4.0-pro` | | [Rerank 4 Fast](https://openrouter.ai/cohere/rerank-4-fast) | `cohere/rerank-4-fast` | `rerank-v4.0-fast` | | [Rerank v3.5](https://openrouter.ai/cohere/rerank-v3.5) | `cohere/rerank-v3.5` | `rerank-v3.5` | | [Command A+](https://openrouter.ai/cohere/command-a-plus) | `cohere/command-a-plus` | `command-a-plus-05-2026` | | [Command A](https://openrouter.ai/cohere/command-a) | `cohere/command-a` | `command-a-03-2025` | | [Command R+ (08-2024)](https://openrouter.ai/cohere/command-r-plus-08-2024) | `cohere/command-r-plus-08-2024` | `command-r-plus-08-2024` | | [Command R (08-2024)](https://openrouter.ai/cohere/command-r-08-2024) | `cohere/command-r-08-2024` | `command-r-08-2024` | | [Command R7B (12-2024)](https://openrouter.ai/cohere/command-r7b-12-2024) | `cohere/command-r7b-12-2024` | `command-r7b-12-2024` | | [North Mini Code](https://openrouter.ai/cohere/north-mini-code) | `cohere/north-mini-code:free` | `north-mini-code-1.0` | For pricing, see each model's OpenRouter page. For model details, see the [models overview](/v1/docs/models). ## Setup checklist 1. Create an OpenRouter account and an [API key](https://openrouter.ai/settings/keys), and set the key as the `OPENROUTER_API_KEY` environment variable. 2. Install the [OpenRouter Python SDK](https://openrouter.ai/docs/client-sdks/python/overview) with `pip install openrouter` (Python 3.10 or later; [source on GitHub](https://github.com/OpenRouterTeam/python-sdk)), or call OpenRouter's HTTP API directly. 3. Choose a model from the table above and pass its OpenRouter model ID as the `model` parameter. Each model's OpenRouter page includes example requests. 4. Call the API for the model type: * Command and North models: [Chat](https://openrouter.ai/docs/client-sdks/python/sdks/chat/README) * Embed models: [Embeddings](https://openrouter.ai/docs/client-sdks/python/sdks/embeddings/README) * Rerank models: [Rerank](https://openrouter.ai/docs/client-sdks/python/sdks/rerank/README) 5. To combine embeddings, reranking, and generation in one pipeline, follow OpenRouter's [RAG cookbook](https://openrouter.ai/docs/cookbook/evaluate-and-optimize/rag). ## Differences from the Cohere API OpenRouter's APIs use OpenRouter's request and response formats rather than Cohere's, and support a subset of the Cohere API's parameters: * **Chat**: OpenRouter's chat API is OpenAI-compatible. Supported parameters vary by model; for example, tool use (`tools`) is available for Command A+, Command R+ (08-2024), Command R (08-2024), and North Mini Code, but not for Command A or Command R7B. * **Embeddings**: OpenRouter supports `input`, `input_type`, `dimensions`, and `encoding_format` (`float` or `base64`). Embeddings are returned in `data[].embedding`. To embed images, use OpenRouter's [multimodal input format](https://openrouter.ai/docs/api_reference/embeddings). For `int8` or `binary` embeddings, use the [Cohere Embed API](/v1/reference/embed). * **Rerank**: OpenRouter supports `query`, `documents`, and `top_n`. Results are returned in `results[]`, each with an `index`, `relevance_score`, and `document`. [Context Focus](/v1/docs/rerank#context-focus) (`relevant_spans`) isn't part of OpenRouter's Rerank API; to use it, call the [Cohere Rerank API](/v1/reference/rerank).