thenlper/gte-large
deepinfra
This large-scale text embedding model excels at converting documents and queries into dense vector representations for semantic search, retrieval-augmented generation, and similarity matching tasks, making it ideal for developers and researchers building information retrieval systems and AI applications that require precise semantic understanding.
- Context window
- — tokens
- Input cost
- —
- Output cost
- —
- Latency (p50)
- 1655 ms
