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Español(ES) Cómo correr un modelo de 180B sin GPU: POCKET-Darwin-180B en GGUF con llama.cpp

180B parameter AI model runs on consumer hardware via quantization

By PulseAugur Editorial · [1 sources] ·

A quantized version of the Darwin-180B-RSI model, named POCKET-Darwin-180B-GGUF, has been released, allowing it to run on consumer hardware without a dedicated GPU. This 111 GB model utilizes a Mixture of Experts (MoE) architecture, meaning only a fraction of its 180 billion parameters are active for each token generation. The model can achieve up to 21 tokens per second on a CPU with sufficient RAM, or slower speeds on laptops with less RAM by leveraging SSDs for weight loading, while maintaining the original model's precision. AI

IMPACT Enables running large language models on consumer hardware, reducing reliance on cloud GPUs.

RANK_REASON Release of a quantized, open-source model for local inference.

Read on dev.to — LLM tag →

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

180B parameter AI model runs on consumer hardware via quantization

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18 / 100
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Tool
Release of a quantized, open-source model for local inference.
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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, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 Español(ES) · 김민식/학생 ·

    How to run a 180B model without a GPU: POCKET-Darwin-180B in GGUF with llama.cpp

    <h2> TL;DR </h2> <p>POCKET-Darwin-180B-GGUF es la versión cuantizada del modelo abierto Darwin-180B-RSI, pensada para correr sin GPU. Puntos clave para quien va a desplegarlo:</p> <ul> <li> <strong>Pesa 111 GB</strong> en GGUF (el original en BF16 ocupa 360 GB) y se ejecuta con <…

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