# text-embedding-3-small Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/text-embedding-3-small
> Markdown URL: https://aitinkerers.org/technologies/text-embedding-3-small.md
> Technology record last updated: 2026-03-10T19:33:05Z
> Generated: 2026-10-23T13:54:52Z

This is the premier, cost-optimized embedding model: superior performance over `ada-002` at an 80% lower cost.

The `text-embedding-3-small` model is the new baseline for high-efficiency vector generation (1536 dimensions by default). It delivers a massive cost reduction: $0.02 per million tokens, down from the predecessor's $0.10. Performance is substantially improved, showing a 13-point gain on the MIRACL multilingual benchmark. Crucially, it incorporates Matryoshka Representation Learning (MRL): this allows you to truncate the vector to smaller sizes (e.g., 512 dimensions) for faster search and reduced storage, all while retaining core semantic integrity. Deploy this model for high-volume semantic search, clustering, and RAG applications.

- Official technology site: https://platform.openai.com/docs/guides/embeddings
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Ho Jiak Bo: a food recommender app based on top food blogs](https://singapore.aitinkerers.org/talks/rsvp_agtw4_hzm6k)

- Event context: AI Tinkerers Singapore: May Meetup - May 21st, 2025 — 2025-05-21 — Singapore
- Public talk page: https://singapore.aitinkerers.org/talks/rsvp_agtw4_hzm6k

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