Sentence Transformers: all-MiniLM-L6-v2

sentence-transformers/all-minilm-l6-v2

Created Nov 17, 2025512 context

$0.005/M input tokens$0/M output tokens

The all-MiniLM-L6-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, enabling high-quality semantic representations that are ideal for downstream tasks such as information retrieval, clustering, similarity scoring, and text ranking.

Sentence Transformers: all-MiniLM-L6-v2

sentence-transformers/all-minilm-l6-v2

Created Nov 17, 2025512 context

$0.005/M input tokens$0/M output tokens

The all-MiniLM-L6-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, enabling high-quality semantic representations that are ideal for downstream tasks such as information retrieval, clustering, similarity scoring, and text ranking.

Recent activity on all-MiniLM-L6-v2

Total usage per day on OpenRouter

Prompt

13.7M

Completion

0