Sentence Transformers: all-MiniLM-L12-v2

The all-MiniLM-L12-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as semantic search, clustering, and similarity-scoring.

• Context window: 8,192 tokens
• Input: text
• Output: embeddings
• Pricing: $0.005/M input tokens

View on OpenRouter. Model data sourced from OpenRouter.