# Hugging Face — Train 400x faster Static Embedding Models with Sentence Transformers

- Company: Hugging Face (huggingface.co)
- Announced: 2025-01-15T00:00:00+00:00
- Category: new-model
- Subject: Platform
- Models affected: sentence-transformers/static-retrieval-mrl-en-v1, sentence-transformers/static-similarity-mrl-multilingual-v1
- Source: https://huggingface.co/blog/static-embeddings
- Record: https://forck.live/items/1770-train-400x-faster-static-embedding-models-with-sentence-transformers

Hugging Face introduces a training method for static embedding models that are 100x to 400x faster on CPU than state-of-the-art models while retaining about 85% of performance. They release two models (for English retrieval and multilingual similarity), training scripts, and datasets.

## Evidence

Verbatim from https://huggingface.co/blog/static-embeddings:

> This blog post introduces a method to train static embedding models that run 100x to 400x faster on CPU than state-of-the-art embedding models, while retaining most of the quality.

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