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Liquid AI releases smallest on-device model, LFM2.5-230M

By PulseAugur Editorial · [1 sources] ·

Liquid AI has launched LFM2.5-230M, their most compact model yet. This open-weight model, with 230 million parameters, is designed for on-device operation on edge hardware. It achieves speeds of 213 tokens/s on a Samsung Galaxy S25 Ultra and 42 tokens/s on a Raspberry Pi 5, supporting tool use and data extraction. AI

IMPACT Enables more capable on-device AI applications, particularly for tool use and data extraction on consumer hardware.

RANK_REASON Release of a small, specialized model for on-device inference.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Liquid AI releases smallest on-device model, LFM2.5-230M

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Release of a small, specialized model for on-device inference.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
90 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Liquid AI has released LFM2.5-230M, its smallest model to date. The 230M-parameter open-weight model runs on-device at 213 tokens/s on a Galaxy S25 Ultra and 42

    Liquid AI has released LFM2.5-230M, its smallest model to date. The 230M-parameter open-weight model runs on-device at 213 tokens/s on a Galaxy S25 Ultra and 42 tokens/s on a Raspberry Pi 5. Built for tool use and data extraction on edge hardware. https://www. marktechpost.com/20…

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