Cohere Embed 4 (New)

The cohere.embed-v4.0 is a multimodal model that can create text embeddings either from text inputs or from an image. Image input isn't available in the Console and you must use the API. For API, input a base64 encoded image in each run. For example, a 512 x 512 image is converted to about 1,610 tokens.

Available in These Regions

Brazil East (Sao Paulo) (dedicated AI cluster only)
Germany Central (Frankfurt) (dedicated AI cluster only)
India South (Hyderabad) (dedicated AI cluster only)
Japan Central (Osaka)
Saudi Arabia Central (Riyadh)
UAE East (Dubai) (dedicated AI cluster only)
UK South (London) (dedicated AI cluster only)
US Midwest (Chicago)

Key Features

Mode
- Input text or image, but not both.
- To get embeddings for an image, only one image is allowed. You can't combine text and image for the same embedding. Image input through API only.
Input and Output
- In the Console, each text input must be less than 512 tokens and maximum 96 inputs per run.
- In the SDK and API, all inputs together can add up to 128,000 tokens per embedding per run.
- Model outputs a 1,536-dimensional vector for each embedding.
Language Support
- Text: English or multilingual.
- Image: English only.

Dedicated AI Cluster for the Model

To reach a model through a dedicated AI cluster in any listed region, you must create an endpoint for that model on a dedicated AI cluster. For the cluster unit size that matches this model, see the following table.


Base Model	Fine-Tuning Cluster	Hosting Cluster	Pricing Page Information	Request Cluster Limit Increase
Model Name: Cohere Embed 4 OCI Model Name: `cohere.embed-v4.0`	Not available for fine-tuning	Unit Size: Embed Cohere Required Units: 1	Pricing Page Product Name: Embed Cohere - Dedicated For Hosting, Multiply the Unit Price: x1	Limit Name: `dedicated-unit-embed-cohere-count` For Hosting, Request Limit Increase by: 1

Tip

If you don't have enough cluster limits in your tenancy for hosting an Embed model on a dedicated AI cluster, request the dedicated-unit-embed-cohere-count limit to increase by 1.
Review the Cohere Embed 4 cluster performance benchmarks for different use cases.

Release and Retirement Dates


Model	Release Date	On-Demand Retirement Date	Dedicated Mode Retirement Date
`cohere.embed-v4.0`	2025-07-03	At least 6 months after the release of the 1^st replacement model.	At least 6 months after the release of the 1^st replacement model.

Important

For a list of all model time lines and retirement details, see Retiring the Models.

Embedding Model Parameter

When using the embedding models, you can get a different output by changing the following parameter.

Truncate: Whether to truncate the start or end tokens in a sentence, when that sentence exceeds the maximum number of allowed tokens. For example, a sentence has 516 tokens, but the maximum token size is 512. If you select to truncate the end, the last 4 tokens of that sentence are cut off.