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Colibri language model runs 744B parameters on laptop with 25GB RAM

By PulseAugur Editorial · [2 sources] ·

A new language model called Colibri, based on GLM-5.2, has been developed to run on a laptop with only 25GB of RAM. This model, which boasts 744 billion parameters, utilizes a Mixture-of-Experts (MoE) architecture and achieves its efficiency by activating only around 40 billion parameters at a time. The implementation is written in pure C with no external dependencies, making it highly accessible. AI

IMPACT This development could significantly lower the barrier to entry for running large language models, enabling wider experimentation and deployment on consumer hardware.

RANK_REASON The cluster describes a new model release with technical details about its architecture and resource requirements.

Read on Mastodon — fosstodon.org →

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

Colibri language model runs 744B parameters on laptop with 25GB RAM

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The cluster describes a new model release with technical details about its architecture and resource requirements.
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COVERAGE [2]

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

    RT @chenzeling4: 744B parameters. On a laptop. With 25GB RAM. Colibri runs GLM-5.2 (744B MoE) in pure C with zero dependencies. The trick: only ~40B params acti

    RT @chenzeling4: 744B parameters. On a laptop. With 25GB RAM. Colibri runs GLM-5.2 (744B MoE) in pure C with zero dependencies. The trick: only ~40B params activate per token, so it keeps the dense part resident and streams experts from disk on demand. A single 2,400-line C file.…

    LINKS github.com/…/colibri
  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    RT @chenzeling4: 744B parameters. On a laptop. With 25GB RAM. Colibri runs GLM-5.2 (744B MoE) in pure C with zero dependencies. The trick: only ~40B params acti

    RT @chenzeling4: 744B parameters. On a laptop. With 25GB RAM. Colibri runs GLM-5.2 (744B MoE) in pure C with zero dependencies. The trick: only ~40B params activate per token, so it keeps the dense part resident and streams experts from disk on demand. A single 2,400-line C file.…

    LINKS github.com/…/colibri

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