PulseAugur
EN
LIVE 03:32:48

Gemma 4 26B-A4B model runs on 2GB RAM with Turbo-Fieldfare

The drumih/turbo-fieldfare project has gained significant traction on GitHub, adding over 600 stars to reach a total of 2,900. This project enables inference for the Gemma 4 26B-A4B model using approximately 2 GB of RAM on M-series MacBooks. AI

IMPACT Enables running large models on consumer hardware, potentially lowering barriers to AI experimentation.

RANK_REASON This is a project that enables a model to run on limited hardware, not a release of a new model or foundational research.

Read on Mastodon — fosstodon.org →

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

Gemma 4 26B-A4B model runs on 2GB RAM with Turbo-Fieldfare

COVERAGE [1]

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

    🚀 Also climbing today: ⭐ drumih/turbo-fieldfare +619 stars (total 2.9k) « Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook » https:// olud.ai/p

    🚀 Also climbing today: ⭐ drumih/turbo-fieldfare +619 stars (total 2.9k) « Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook » https:// olud.ai/project/drumih-turbo-f ieldfare.html # OpenSource # AI # GitHub