Cohere Embed v3 Multilingual
Version: 1
Models from Microsoft, Partners, and Community
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- Innovation and agility: Combines Microsoft research models with rapid, community-driven advancements.
- Seamless Azure integration: Standard Azure AI Foundry experience, with support managed by the model provider.
- Flexible deployment: Deployable as Managed Compute or Serverless API, based on provider preference.
Key capabilities
About this model
Cohere Embed Multilingual is the market's leading multimodal (text, image) representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.Key model capabilities
- Semantic search
- Retrieval-augmented generation (RAG)
- Classification
- Clustering
- Multimodal (text, image) representation
- Cross-language search capabilities
- Support for 100+ languages
- Search within a language (e.g., search with a French query on French documents)
- Search across languages (e.g., search with an English query on Chinese documents)
Use cases
See Responsible AI for additional considerations for responsible use.Key use cases
The provider has not supplied this information.Out of scope use cases
Prompts and completions are passed through a default configuration of Azure AI Content Safety classification models to detect and prevent the output of harmful content. Learn more about Azure AI Content Safety . Configuration options for content filtering vary when you deploy a model for production in Azure AI; learn more .Pricing
Pricing is based on a number of factors, including deployment type and tokens used. See pricing details here.Technical specs
The provider has not supplied this information.Training cut-off date
The provider has not supplied this information.Training time
The provider has not supplied this information.Input formats
The provider has not supplied this information.Output formats
The provider has not supplied this information.Supported languages
Embed Multilingual supports 100+ languages.Sample JSON response
The provider has not supplied this information.Model architecture
The provider has not supplied this information.Long context
The provider has not supplied this information.Optimizing model performance
The provider has not supplied this information.Additional assets
Embed multilingual has SOTA performance on multilingual benchmarks such as Miracl and the multilingual evaluation results can be found in the following Embed v3.0 Miracl Evaluation Results and full MTEB results can be found in the following Embed v3.0 MTEB Evaluation Results . Evaluations against multi-modal embedding models can be found in the following Embed v3.0 Multimodal Evaluation Results .Training disclosure
Training, testing and validation
This model was trained on nearly 1B English training pairs and nearly 0.5B Non-English training pairs from 100+ languages.Distribution
Distribution channels
The provider has not supplied this information.More information
The provider has not supplied this information.Responsible AI considerations
Safety techniques
Prompts and completions are passed through a default configuration of Azure AI Content Safety classification models to detect and prevent the output of harmful content. Learn more about Azure AI Content Safety . Configuration options for content filtering vary when you deploy a model for production in Azure AI; learn more .Safety evaluations
The provider has not supplied this information.Known limitations
The provider has not supplied this information.Acceptable use
Acceptable use policy
The provider has not supplied this information.Quality and performance evaluations
Source: Cohere Embed multilingual has SOTA performance on multilingual benchmarks such as Miracl and the multilingual evaluation results can be found in the following Embed v3.0 Miracl Evaluation Results and full MTEB results can be found in the following Embed v3.0 MTEB Evaluation Results . Evaluations against multi-modal embedding models can be found in the following Embed v3.0 Multimodal Evaluation Results .Benchmarking methodology
Source: Cohere The provider has not supplied this information.Public data summary
Source: Cohere The provider has not supplied this information.Model Specifications
Context Length512
LicenseCustom
Last UpdatedAugust 2025
Input TypeText
Output TypeEmbeddings
ProviderCohere
Languages10 Languages