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Italiano(IT) Flint è un modello MoE da 40 miliardi di parametri progettato per il coding locale. Attivando solo 2,5 miliardi di parametri per token, raggiunge i 125 token al

Flint MoE model achieves 125 tokens/sec for local coding

By PulseAugur Editorial · [1 sources] ·

Flint is a 40 billion parameter Mixture-of-Experts (MoE) model specifically designed for local coding tasks. It achieves a speed of 125 tokens per second on a MacBook Pro M4 Pro by activating only 2.5 billion parameters per token, outperforming equivalent dense models. The model was developed in under four months by Eureka Machine. AI

IMPACT Offers a faster, locally-run coding assistant, potentially improving developer workflows and privacy.

RANK_REASON Release of a new open-source model with performance metrics. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — fosstodon.org →

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

Flint MoE model achieves 125 tokens/sec for local coding

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Release of a new open-source model with performance metrics. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 Italiano(IT) · [email protected] ·

    Flint is a 40B parameter MoE model designed for local coding. Activating only 2.5B parameters per token, it reaches 125 tokens/s

    Flint è un modello MoE da 40 miliardi di parametri progettato per il coding locale. Attivando solo 2,5 miliardi di parametri per token, raggiunge i 125 token al secondo su MacBook Pro M4 Pro, superando per velocità i modelli densi equivalenti. Sviluppato in meno di quattro mesi c…

    LINKS testingcatalog.com/recursive-releases-fli…

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