Release Notes

We’re pleased to announce the release of Embed 5, Cohere’s most powerful embeddings family yet.

Embed 5 delivers frontier retrieval quality on complex enterprise data, with major gains over Embed 4 on visually rich documents, financial filings, parsed PDFs, code, and multilingual retrieval.

Key features

• Two model variants available:
  • embed-v5.0-pro: Optimized for the highest retrieval quality, particularly for offline indexing and quality-critical retrieval
  • embed-v5.0-fast: Optimized for low latency and high throughput, particularly for interactive search, agent loops, and high-volume query traffic
• Shared embedding space: Pro and Fast share an embedding space, so a corpus indexed with one model can be queried with the other. We recommend indexing with Pro and querying with Fast.
• Multimodal inputs: Embed text, images, and mixed text-and-image inputs (e.g. PDF pages) in a single vector
• Multilingual support: Supports over 100 languages
• Extended context length: 128k token context window
• Flexible storage: Matryoshka embeddings in the following dimensions: [256, 512, 768, 1024, 1536, 2048], with float, int8, and binary output types

Availability

Embed 5 is available through the Embed API, as well as Microsoft Foundry and Amazon SageMaker. For single-tenant deployment, Embed 5 is also available in Model Vault.

For more details, see the model documentation.