OpenAI
OpenAI: Text Embedding 3 Small
openai/text-embedding-3-small
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. 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.
Input
$0.02
/ 1M tokens · Token reference
Output
$0
/ 1M tokens · Token reference
Context window
8.19K
tokens
Embeddings output · Token reference fields do not establish an output-unit price.
Limits
Context
8,192
tokens
Max output
7,372
90% of the context window
Model facts
Author
OpenAI
Tokenizer
Other
Modality
Text -> Embeddings
Created
Oct 30, 2025
Publication status
Hugging Face: unavailableLicense: not publishedParameter count: not published
Modalities
Input · TextOutput · Embeddings