# granite-embedding 278m Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/granite-embedding-278m
> Markdown URL: https://aitinkerers.org/technologies/granite-embedding-278m.md
> Technology record last updated: 2026-09-18T15:13:51Z
> Generated: 2026-10-23T14:58:50Z

IBM's high-efficiency 278M parameter model optimized for multilingual text embeddings and high-performance RAG workflows.

The granite-embedding 278m model delivers a lean, high-performance solution for dense vector retrieval across 38 languages. Built on a transformer architecture with a 512-token context window, it balances a compact 278-million parameter footprint with state-of-the-art accuracy on the MTEB benchmark. IBM engineered this model specifically for Retrieval-Augmented Generation (RAG) tasks, ensuring low-latency inference and precise semantic search capabilities for enterprise AI pipelines.

- Official technology site: https://huggingface.co/ibm-granite/granite-embedding-278m-multilingual
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Compose and Dragons: Tiny Language Models in Action](https://paris.aitinkerers.org/talks/rsvp_lNiq-CojExE)

- Event context: AI Tinkerers Paris: Docker Agentic Workflows (Devoxx Kickoff) — 2026-04-21 — Paris
- Public talk page: https://paris.aitinkerers.org/talks/rsvp_lNiq-CojExE

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