> This page is for version v2 API (default).
> 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.

# Embed 5 and Rerank 5 Are Now Available on OpenRouter

> Cohere's Embed 5 and Rerank 5 models, in Pro and Fast variants, are now available on OpenRouter through its Embeddings and Rerank APIs.

Cohere's [Embed 5](/docs/cohere-embed) and [Rerank 5](/docs/rerank) models are now available on
[OpenRouter](https://openrouter.ai/cohere). If you build on OpenRouter, you can now add Cohere embeddings and reranking
to your search and RAG pipelines with your existing OpenRouter API key.

## Available models

* [Embed 5 Pro](https://openrouter.ai/cohere/embed-5-pro) (`cohere/embed-5-pro`): Optimized for the highest retrieval
  quality, particularly for offline indexing and quality-critical retrieval.
* [Embed 5 Fast](https://openrouter.ai/cohere/embed-5-fast) (`cohere/embed-5-fast`): Optimized for low latency and high
  throughput, particularly for interactive search, agent loops, and high-volume query traffic.
* [Rerank 5 Pro](https://openrouter.ai/cohere/rerank-5-pro) (`cohere/rerank-5-pro`): Optimized for the highest ranking
  quality, particularly for complex, reasoning-heavy queries and long or domain-specific documents.
* [Rerank 5 Fast](https://openrouter.ai/cohere/rerank-5-fast) (`cohere/rerank-5-fast`): Rerank 5 quality for latency-
  and cost-sensitive workloads. Outperforms Rerank 4 Pro.

Embed 5 accepts text, images, and mixed text-and-image inputs such as PDF pages. Embed 5 Pro and Fast share an
embedding space, so you can index your corpus with Pro and embed queries with Fast.

For pricing, see each model's OpenRouter page.

## Getting started

See [Using Cohere Models on OpenRouter](/docs/cohere-on-openrouter) for the full list of Cohere models on OpenRouter, a
setup checklist, and the differences from the Cohere API. For an end-to-end retrieval pipeline, see OpenRouter's
[RAG with Embeddings & Rerank](https://openrouter.ai/docs/cookbook/evaluate-and-optimize/rag) cookbook.

For more on the models themselves, see the [Embed 5 announcement](/changelog/embed-v5) and the
[Rerank 5 announcement](/changelog/rerank-v5).