Intfloat: E5-Base-v2

The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as semantic search, similarity scoring, retrieval and clustering.

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

View on OpenRouter. Model data sourced from OpenRouter.