BAAI/bge-m3
sentence-similarity model by BAAI
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
For more details please refer to our github repo: https://github.com/FlagOpen/FlagEmbedding In this project, we introduce BGE-M3, which is distinguished for its versatility in Multi-Functionality, Multi-Linguality, and Multi-Granularity. Some suggestions for retrieval pipeline in RAG We recommend to use the following pipeline: hybrid retrieval + re-ranking. A classic example: using both embedding retrieval and the BM25 algorithm. Now, you can try to use BGE-M3, which supports both embedding and sparse retrieval. This allows you to obtain token weights (similar to the BM25) without any additional cost when generate dense embeddings. To use hybrid retrieval, you can refer to Vespa and Milvus. Utilizing the re-ranking model (e.g., bge-reranker, bge-reranker-v2) after retrieval can further filter the selected text. Details The previous test results were lower because we mistakenly removed the passages that have the same id as the query from the search results. After correcting this mistake, the overall performance of BGE-M3 on…
Read the full model card ↗ · Preview checked 2026-10-27T22:13:47.108Z
Inside the original model card — Document outline
- BGE-M3 (paper, code)
- News:
- Specs
- FAQ
- Usage
- Generate Embedding for text
- Compute score for text pairs
- Evaluation
- Benchmarks from the open-source community
- Our results
- Training
- Acknowledgement
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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
BAAI/bge-m3 is a sentence-similarity model repository published by BAAI on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 30,192,732
- Cumulative likes
- 3,948
- Hugging Face trending score
- 17
- Reported safetensors parameters
- Not reported
- Architecture
- XLMRobertaModel
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2024-01-27T17:07:29.000Z
- Last modified
- 2024-07-03T14:50:10.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-31T06:53:30.698Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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