Thenlper: GTE-Base

The gte-base embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, delivering efficient and effective semantic embeddings optimized for textual similarity, semantic search, and clustering applications.

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

View on OpenRouter. Model data sourced from OpenRouter.