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Liquid AI released two retrieval models

2026-06-18 · 15:30 UTC ·@ramin_m_h ·0 min read

Brief

Liquid AI announced two 350M-parameter retrieval models—LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M—positioned for ultra-fast, accurate multilingual search. The company claims an end-to-end retrieval latency down to 1.5 ms on its enterprise stack and asserts best-in-class multilingual and cross-lingual performance across 11 languages, including Arabic, English, Japanese, Korean, and several European languages.

Why it matters

Liquid AI released two retrieval models: LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M (both 350M-parameter variants).

Key details

  • They claim end-to-end retrieval latency as low as 1.5 ms when deployed with their enterprise stack.
  • Models target multilingual and cross-lingual search with reported best-in-class performance across 11 languages: Arabic, German, English, Spanish, French, Italian, Japanese, Korean, Norwegian, Portuguese, and Swedish.
Source evidence

1.5ms end-to-end retrieval latency ✨

Liquid AI (@liquidai)

Introducing LFM2.5-Embedding-350M and LFM2.5-ColBERT-350M: two multilingual retrieval models built for ultra-fast and accurate search across 11 languages.

> End-to-end retrieval latency as low as 1.5ms with our enterprise stack! 🚀

> Consistently best-in-class multilingual and cross-lingual performance across Arabic, German, English, Spanish, French, Italian, Japanese, Korean, Norwegian, Portuguese, and Swedish.

🧵

— https://nitter.net/liquidai/status/2067610173024219225#m