Text · BAAI
bge-m3
BAAI's bge-m3 embedding model for search. It turns text into vectors. It does not chat. The fit row should be an easy pass on almost any current machine.
Freshness uses the repository open date. This record is 1009 days old, opened 2024-01-27. Popularity uses 30,351,006 downloads and 3,949 likes listed by Hugging Face. Checked 2026-11-01. Neither number grades answers. Formulas.
This model embeds or reranks text for search. It is not a chat model.
Hugging Face reports 13.7 GB of storage for the whole repository. That figure can include several packs, so the fit table does not use it as the size of one file.
Will it fit?
Save a machine on the hardware page and this block fills in. The table already has the sizes.
| Pack | Size | Saved machine |
|---|---|---|
| Largest published checkpoint | 2.3 GB weights + 1.0 GB allowance. File: pytorch_model.bin. | Choose a machine |
Estimate rows use the parameter count. A measured row names a file in the repository. The allowance is fixed: it stands in for context or activations, and it is not a measurement from a run.
How to run it
Text models are usually loaded from a quantized pack in llama.cpp, Ollama, or LM Studio, or from the original weights with the publisher's own instructions. AI Price Desk does not host the weights.
Publisher repository on Hugging Face
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This directory is assembled from public model records. Freshness is age. Popularity is downloads and likes. A fit figure is an estimate from a parameter count or from a published file size, not a run on our hardware. How the numbers are made. AI disclosure.