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DeepSeek 284B model runs on 64GB CPU via llama-modchip

By PulseAugur Editorial · [1 sources] ·

Synchopate has released llama-modchip v2.4.0, a tool that enables the 284B DeepSeek-V4-Flash model to run on a 64GB CPU system without GPUs. This is achieved through a custom tensor type and a patched llama.cpp fork, allowing the model and its KV cache to fit within standard workstation RAM. While this represents a significant advancement for local inference, particularly for offline coding agents and long-context tasks, it does not address the latency bottlenecks inherent in Windows audio processing for real-time applications. AI

IMPACT Enables running large models on consumer-grade hardware, potentially democratizing local AI applications.

RANK_REASON This item details a software tool that enables a large language model to run on less powerful hardware, which is a significant development for local inference capabilities.

Read on dev.to — LLM tag →

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

DeepSeek 284B model runs on 64GB CPU via llama-modchip

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54 / 100
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Tool
This item details a software tool that enables a large language model to run on less powerful hardware, which is a significant development for local inference capabilities.
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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.
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infra, model release
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · devs ·

    Llama-modchip Puts 284B DeepSeek on 64GB CPU — Agents Still Starve on the Windows Capture Path

    <p>Synchopate’s llama-modchip (v2.4.0) claims to run DeepSeek-V4-Flash — 284.33B total parameters, 13.17B active — on a pure 64 GB CPU system with zero GPUs. The compressed GGUF is 56.56 GiB (1.71 bpw via SwiGLU-H2 + Fractal-64), peak VmRSS stays under 59 GiB at 256K context, and…

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