sentence-transformers / sentence-similarity updated 2 months ago

all-MiniLM-L6-v2

Name: all-MiniLM-L6-v2
Author: sentence-transformers

This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search.

Params

20 M

Context

512

Downloads 30d

257.8 M

Likes

5,182

Commercial use: allowed apache-2.0 Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

259.6 M251.1 M

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	f32	0.1 GB	0.6 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: BertModel
Parameters: 20 M
Tensor type: F32
Context length: 512
Vocabulary: 30,522
Layers / heads: 6 / 12
Licence: apache-2.0
First seen on the Hub: 2022-03-02
Training datasets: s2orc, flax-sentence-embeddings/stackexchange_xml, ms_marco, gooaq, yahoo_answers_topics, code_search_net, search_qa, eli5, snli, multi_nli, wikihow, natural_questions, trivia_qa, embedding-data/sentence-compression, embedding-data/flickr30k-captions, embedding-data/altlex, embedding-data/simple-wiki, embedding-data/QQP, embedding-data/SPECTER, embedding-data/PAQ_pairs, embedding-data/WikiAnswers
Added to our catalog: 2026-07-28

Family

Base model and the most-downloaded derivatives in the catalog.

Derivative all-MiniLM-L6-v2 Xenova 2.9 M

Compare with

paraphrase-multilingual-MiniLM-L12-v2 59.4 M bge-m3 35.0 M all-mpnet-base-v2 25.2 M multilingual-e5-small 15.6 M paraphrase-MiniLM-L6-v2 2.8 M paraphrase-MiniLM-L3-v2 2.6 M

Appears in

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