Cohere Embed Multilingual Light Image 3

The cohere.embed-multilingual-light-image-v3.0 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)
Japan Central (Osaka) (dedicated AI cluster only)
UAE East (Dubai) (dedicated AI cluster only)
UK South (London) (dedicated AI cluster only)
US East (Ashburn) (dedicated AI cluster only)
US Midwest (Chicago) (dedicated AI cluster only)

Access this Model

Access this model through the Console, API, and the CLI:

Key Features

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.
Light models are smaller and faster than the original models.
English or multilingual.
Model creates a 384-dimensional vector for each embedding.
Maximum 128,000 tokens per embedding.
In the Console, input a .png or .jpg image of 5 MB or less.
For API, input a base64 encoded image in each run. For example, a 512 x 512 image is converted to about 1,610 tokens.
Use the Cohere Embed Multilingual models when:
- Instead of English, the documents are written in one of the supported languages.
- The documents are written in more than one language and those languages are one of the supported languages.

On-Demand Mode

The cohere.embed-multilingual-light-image-v3.0 model isn't available in the on-demand mode.

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 Multilingual Light Image 3 OCI Model Name: `cohere.embed-multilingual-light-image-v3.0`	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.

Endpoint Rules for Clusters

A dedicated AI cluster can hold up to 50 endpoints.
Use these endpoints to create aliases that all point either to the same base model or to the same version of a custom model, but not both types.
Several endpoints for the same model make it easy to assign them to different users or purposes.


Hosting Cluster Unit Size	Endpoint Rules
Embed Cohere	Base model: To run the `cohere.embed-multilingual-light-image-v3.0` model on several endpoints, create as many endpoints as you need on a Embed Cohere cluster (unit‑size). Custom model: You can't fine‑tune `cohere.embed-multilingual-light-image-v3.0`, so you can't create and host custom models built from that base.

Tip

To increase the call volume supported by a hosting cluster, increase its instance count by editing the dedicated AI cluster. See Updating a Dedicated AI Cluster.
For more than 50 endpoints per cluster, request an increase for the limit, endpoint-per-dedicated-unit-count. See Requesting a Service Limit Increase and Service Limits for Generative AI.

Cluster Performance Benchmarks

Review the Cohere Embed Multilingual Light Image 3 cluster performance benchmarks for different use cases.

Release and Retirement Dates


Model	Release Date	On-Demand Retirement Date	Dedicated Mode Retirement Date
`cohere.embed-multilingual-light-image-v3.0`	2025-05-14	On-demand mode isn't available for this model.	`2026-01-22`

Important

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

Input Data for Text Embeddings

Input data for creating text embeddings has the following requirements:

You can add sentences, phrases, or paragraphs for embeddings either one phrase at a time, or by uploading a file.
Only files with a .txt extension are allowed.
If you use an input file, each input sentence, phrase, or paragraph in the file must be separated with a newline character.
A maximum of 96 inputs are allowed for each run.
In the Console, each input must be less than 512 tokens for the text only models.
If an input is too long, select whether to cut off the start or the end of the text to fit within the token limit by setting the Truncate parameter to Start or End. If an input exceeds the 512 token limit and the Truncate parameter is set to None, you get an error message.
For the text and image models, you can have files and inputs that all add up to 128,000 tokens.
For the text and image embed models, such as Cohere Embed English Image V3 you can either add text or add one image only. For the image, you can use API. Image input isn't available in the Console. For API, input a base64 encoded image in each run. For example, a 512 x 512 image is converted to about 1,610 tokens.

Learn about Creating text embeddings in OCI Generative AI.

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.

Oracle Cloud Infrastructure Documentation