TextEmbeddingAda3Large
text-embedding-3-large is currently the most capable embedding model for both english and non-english tasks.
Currently provides best embedding quality; supports multiple dimensions for flexibility and cost tradeoff.
Outputs: 3072-dimensional vectors (or 256-/512-/1024-dimensional vectors, optionally) Max input tokens: 8191 Released: Jan 2024
Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.