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When to use it

text-embedding-3-small is a compact dense text embedding model from OpenAI. Pinecone offers it for integrated embedding on document indexes, so you upsert and search with text and Pinecone embeds it through Microsoft Azure.

Inputs, limits, and pricing

Monthly and per-minute limits depend on your plan. See Rate limits.

Quickstart

Installation

Integrated embedding on document indexes requires Python SDK 10.1.0, Node.js SDK 9.1.0, or Go SDK 7.1.0 or later.

Create index

This creates a document index whose chunk_text field embeds with text-embedding-3-small at its default 1,536 dimensions.

Embed & upsert

Upsert documents with plain text on the embedded field. Pinecone embeds each value on write, up to 96 documents per request.

Query

Search with an embed clause, and Pinecone embeds the query text with the same model.

Good to know

  • Dimension: 1,536 by default, or any integer from 1 to 1,536. The dimension is fixed when you create the index.
  • Processing location: global (default) or us. The Starter and Builder plans can use only global. See Processing locations.
  • Availability: Integrated embedding on document indexes only, on every plan.