SHELFCRITTER AI Digest

COMPANY

Liquid AI

companytopic-noteopen-sourcefoundation-models

Overview

Liquid AI is a non-OpenAI foundation-model lab building efficient sparse-MoE small models for on-device and cost-sensitive inference, where the active-parameter envelope is the binding constraint.

Timeline

  • 2026-05-30-AI-Digest — Liquid AI announces LFM2.5, an 8B-parameter mixture-of-experts with 1B active params, trained on 38T tokens (Liquid AI blog). Reached HN front page at 170 pts / 62 comments. Why it matters: another efficient sparse-MoE small model from a non-OpenAI lab — relevant for on-device and cost-sensitive inference where the active-parameter envelope is the binding constraint.

Key Developments

  1. LFM2.5 — 8B-A1B MoE on 38T Tokens (May 30, 2026): 8B total / 1B active mixture-of-experts trained on 38T tokens, positioned for on-device and cost-sensitive inference. The active-parameter envelope (1B) is the binding constraint for the target deployment surface; the 38T-token training run is the magnitude signal (2026-05-30-AI-Digest).

See also: LFM2.5, MOC - Open Source Models.