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MiniMax H3 model runs on consumer hardware with system RAM offload

By PulseAugur Editorial · [1 sources] ·

A user has successfully run the MiniMax H3 model by offloading layers to system memory, utilizing 16GB of VRAM and 32GB of DDR5 RAM. The user has provided a GitHub repository with instructions and configurations for reproducing the run on RDNA 4 hardware. They are seeking feedback from others who test the model on different RDNA 4 cards or achieve improved token speeds with alternative offload settings. AI

IMPACT Demonstrates a method for running large models on consumer hardware by leveraging system RAM, potentially lowering barriers to entry for AI experimentation.

RANK_REASON User-level technical demonstration of running a model with system RAM offload, not a frontier release or significant industry event.

Read on r/StableDiffusion →

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

MiniMax H3 model runs on consumer hardware with system RAM offload

How we ranked this

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11 / 100
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Newsworthiness bucket
Tool
User-level technical demonstration of running a model with system RAM offload, not a frontier release or significant industry event.
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Single-source cluster
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/NigaTroubles ·

    Running MiniMax H3 on an RX 9070 XT + 32GB DDR5 RAM

    <!-- SC_OFF --><div class="md"><p>I offloaded the extra layers to system memory so the model fits across 16GB of VRAM and 32GB of DDR5 RAM (⁠[BF16 / quant]⁠).</p> <p>Everything needed to reproduce the run on RDNA 4, including the launch flags and configs, is in this repo:<br /> <…

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