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Liquid AI releases 6 open-weight 2B multimodal models, LFM3

By PulseAugur Editorial · [2 sources] ·

Liquid AI has launched LFM3, a new family of six open-weight, 2B-class multimodal models. These models, built on a shared backbone, are designed for text, vision, audio, and decision-making tasks, with some capable of handling omni-modal inputs. Notably, the LFM3 models require minimal memory, allowing them to run on devices like phones and laptops, and offer competitive performance against larger models on various benchmarks. AI

IMPACT Enables deployment of capable multimodal models on low-resource devices, potentially democratizing AI applications.

RANK_REASON Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Liquid AI releases 6 open-weight 2B multimodal models, LFM3

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60 / 100
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Significant
Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=2 ai=1.0]
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2 independent sources
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Topics
model release, product
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [2]

  1. MarkTechPost TIER_1 English(EN) · Asif Razzaq ·

    Liquid AI Releases LFM3: 6 Open-Weight 2B-Class Multimodal Models

    <p>Liquid AI released LFM3, 6 open-weight 2B-class models for text, vision, audio, omni and decisions. LFM3-1.7B uses a tri-hybrid backbone, a 256K context window and fits in about 1 GB at 4-bit.</p> <p>The post <a href="https://www.marktechpost.com/2026/10/27/liquid-ai-lfm3-open…

  2. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    📰 Liquid AI Releases LFM3: 6 Open-Weight 2B-Class Multimodal Models Liquid AI released LFM3, 6 open-weight 2B-class models for text, vision, audio, omni and dec

    📰 Liquid AI Releases LFM3: 6 Open-Weight 2B-Class Multimodal Models Liquid AI released LFM3, 6 open-weight 2B-class models for text, vision, audio, omni and decisions. LFM3-1.7B uses a tri-hybrid backbone, a 256K context window and fits in about 1 GB at 4-bit. 📰 Source: MarkTechP…

    LINKS marktechpost.com/…/liquid-ai-lfm3-open-we…

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