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Liquid AI releases LFM2-24B-A2B, an efficient 24B parameter MoE model

Liquid AI has released an early checkpoint of its LFM2-24B-A2B model, a sparse Mixture of Experts (MoE) architecture with 24 billion total parameters and 2 billion active parameters per token. This model demonstrates that the LFM2 architecture effectively scales to larger sizes, with consistent quality gains observed across benchmarks as the family has grown. Designed to fit within 32GB of RAM, LFM2-24B-A2B is intended for deployment on both cloud and edge environments, including consumer laptops and desktops. AI

IMPACT Provides an edge-deployable MoE model that balances parameter count with active parameters for efficient inference.

RANK_REASON Release of an open-weight model with detailed architecture and benchmark information, but not from a top-tier frontier lab.

Read on Hacker News — AI stories ≥50 points →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

Liquid AI releases LFM2-24B-A2B, an efficient 24B parameter MoE model

COVERAGE [3]

  1. Hacker News — AI stories ≥50 points TIER_1 English(EN) · nateb2022 ·

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture

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

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www. liquid.ai/blog/lfm2-24b-a2b # HackerNews # LFM2 # Architecture # Scaling # AI # Technology # Innovat

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www. liquid.ai/blog/lfm2-24b-a2b # HackerNews # LFM2 # Architecture # Scaling # AI # Technology # Innovation

  3. Mastodon — mastodon.social TIER_1 English(EN) · CuratedHackerNews ·

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www. liquid.ai/blog/lfm2-24b-a2b # ai

    LFM2-24B-A2B: Scaling Up the LFM2 Architecture https://www. liquid.ai/blog/lfm2-24b-a2b # ai