Sentence Transformers: all-mpnet-base-v2

The all-mpnet-base-v2 embedding model encodes sentences and short paragraphs into a 768-dimensional dense vector space, providing high-fidelity semantic embeddings well suited for tasks like information retrieval, clustering, similarity scoring, and text ranking.

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

View on OpenRouter. Model data sourced from OpenRouter.