BGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval), and Multi-Granularity (handling inputs from short queries to long documents). It achieves state-of-the-art retrieval performance across diverse benchmarks while maintaining a single model for multiple retrieval modes. Inputs to this endpoint are truncated to 512 tokens.
https://api.deepinfra.com/v1/openai/v1/embeddings| Model | Context | Max out |
|---|---|---|
| bge-base-en-v1.5 | — | — |
| bge-en-icl | — | — |
| bge-large-en-v1.5 | — | — |
| bge-m3-multi | — | — |
| bge-m3 | — | — |
/v1/models/deepinfra/BAAI/bge-m3-multiBGE-M3 is a multilingual text embedding model developed by BAAI, distinguished by its Multi-Linguality (supporting 100+ languages), Multi-Functionality (unified dense, multi-vector, and sparse retrieval), and Multi-Granularity (handling inputs from short queries to long documents). It achieves state-of-the-art retrieval performance across diverse benchmarks while maintaining a single model for multiple retrieval modes. Inputs to this endpoint are truncated to 512 tokens.