embed-english-light-v3.0
cohere
This lightweight text embedding model excels at converting English text into numerical vectors for semantic search, clustering, and similarity tasks with minimal computational overhead, making it ideal for developers and organizations seeking cost-effective embedding solutions for applications with resource constraints or latency requirements.
- Context window
- 512 tokens
- Input cost
- —
- Output cost
- —
- Latency (p50)
- —
