Multilingual Embedding 002
Multilingual Embedding 002 is Google's embedding model specifically optimized for cross-lingual retrieval and multilingual document processing. It produces 768-dimensional vectors that align semantically across languages, enabling queries in one language to retrieve relevant documents in any supported language.
This model is essential for global organizations that need to search across multilingual document collections without requiring translation as a preprocessing step.
Key Features
Cross-lingual semantic alignment
100+ language support
768-dimensional vectors
Query-document language independence
Optimized for multilingual retrieval
Ideal Use Cases
Cross-lingual document search
Multilingual knowledge base retrieval
Global enterprise information retrieval
Language-independent content similarity
Example Prompts for Multilingual Embedding 002
Technical Specifications
| Dimensions | 768 |
| Modality | Text → Embedding |
| Provider | |
| Category | Embedding |
| Languages | 100+ |
| Specialty | Cross-lingual retrieval |
Frequently Asked Questions
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