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Liquid AI releases LFM2.5-24B-A2B for on-device agents

By PulseAugur Editorial · [1 sources] ·

Liquid AI has released LFM2.5-24B-A2B, an open-weight, 24 billion parameter Mixture-of-Experts model designed for on-device agents. This model activates approximately 2 billion parameters per token and boasts a 131,072-token context window. It demonstrates strong performance on agentic and tool-use benchmarks, outperforming larger models in specific tasks like AutomationBench, while larger models like Qwen3.6-35B-A3B show better results in knowledge and coding tasks. AI

IMPACT Enables more capable AI agents to run directly on consumer hardware, reducing reliance on cloud services.

RANK_REASON Frontier-lab model release with system card and benchmark data. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on MarkTechPost →

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

Liquid AI releases LFM2.5-24B-A2B for on-device agents

How we ranked this

Signal score
35 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
Frontier-lab model release with system card and benchmark data. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
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, product
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
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

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

    Liquid AI Releases LFM2.5-24B-A2B: A 2B-Active MoE for On-Device Agents

    <p>Liquid AI released LFM2.5-24B-A2B, an open-weight 24B Mixture-of-Experts reasoning model with 2B active parameters. It targets local agents, scoring 48.09 on LiveClaw and decoding 184 tokens/s on an Apple M5 Max.</p> <p>The post <a href="https://www.marktechpost.com/2026/10/14…

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