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Mac users can run Qwen-Image-2.1 with less RAM using staged loading

By PulseAugur Editorial · [1 sources] ·

A user has developed a library called "stageload" to optimize the memory usage of the Qwen-Image-2.1 model on Macs with limited RAM. By loading only the necessary components (text encoder, transformer, VAE) for each stage of the image generation process, the library reduces peak memory consumption from over 43 GB to around 19 GB, preventing system swaps and crashes. This staged loading approach maintains image quality and offers comparable or slightly slower generation times compared to the standard eager loading method, while also reducing initial model loading time. AI

IMPACT Enables running large image generation models on consumer hardware with limited RAM.

RANK_REASON User-developed tool to optimize existing model performance on specific hardware.

Read on r/StableDiffusion →

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

Mac users can run Qwen-Image-2.1 with less RAM using staged loading

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User-developed tool to optimize existing model performance on specific hardware.
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infra, product
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COVERAGE [1]

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

    Qwen-Image-2.1 on a 48 GB Mac: loading the text encoder and the transformer one at a time kept the diffusers pipeline at 19 GB instead of swapping at 43.6 GB

    <table> <tr><td> <a href="https://www.reddit.com/r/StableDiffusion/comments/1wzxdca/qwenimage21_on_a_48_gb_mac_loading_the_text/"> <img alt="Qwen-Image-2.1 on a 48 GB Mac: loading the text encoder and the transformer one at a time kept the diffusers pipeline at 19 GB instead of s…

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