# What vector embedding models work best with Zilliz Cloud Blackwell?

Source: https://zilliz.com/ai-faq/what-vector-embedding-models-work-best-with-zilliz-cloud-blackwell
Author: zilliz

Zilliz Cloud on Blackwell supports all major embedding models (text-embedding-3, CLIP, multilingual variants) with GPU-accelerated inference for real-time embedding generation during search.

## OpenAI text-embedding-3 Integration

Zilliz Cloud can invoke text-embedding-3-large within queries, generating embeddings on-the-fly for real-time search. Blackwell GPU acceleration makes on-the-fly embedding feasible; API latency becomes negligible. Clients send text; Zilliz Cloud returns top-k results in milliseconds.

## Multimodal CLIP Embeddings

Zilliz Cloud supports CLIP for vision-language search. Queries combine text and image embeddings seamlessly. Image-to-text and text-to-image retrieval works with identical indices. Blackwell's throughput handles multimodal batch inference at scale.

## Multilingual Models

Zilliz Cloud supports multilingual embeddings (XLM-R, mBERT variants). A query in English retrieves semantically-similar documents in other languages. Blackwell speeds cross-lingual retrieval significantly.

## Specialized Domain Models

Finance-specialized embeddings (FinBERT) and biomedical embeddings (BioBERT) integrate with Zilliz Cloud. Domain-specific fine-tuning improves relevance; Blackwell acceleration maintains production performance.

## Related Resources

- [Vector embeddings](https://zilliz.com/glossary/vector-embeddings)
- [Zilliz Cloud managed vector database](https://zilliz.com/what-is-zilliz-cloud)