I have done an extensive multi-GPU FLUX Full Fine Tuning / DreamBooth training experimentation on RunPod by using 2x A100–80 GB GPUs (PCIe) since this was commonly asked of me.
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I have done an extensive multi-GPU FLUX Full Fine Tuning / DreamBooth training experimentation on RunPod by using 2x A100–80 GB GPUs (PCIe) since this was commonly asked of me.
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Full article here : 
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Full article here : 
https://medium.com/@furkangozukara/multi-gpu-flux-fu
https://medium.com/@furkangozukara/multi-gpu-flux-fu
link
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Image 1
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Image 1
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Image 1 shows that only first part of installation of Kohya GUI took 30 minutes on a such powerful machine on a very expensive Secure Cloud pod — 3.28 USD per hour
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Image 1 shows that only first part of installation of Kohya GUI took 30 minutes on a such powerful machine on a very expensive Secure Cloud pod — 3.28 USD per hour
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There was also part 2, so just installation took super time
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There was also part 2, so just installation took super time
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On Massed Compute, it would take like 2–3 minutes
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On Massed Compute, it would take like 2–3 minutes
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This is why I suggest you to use Massed Compute over RunPod, RunPod machines have terrible hard disk speeds and they are like lottery to get good ones
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This is why I suggest you to use Massed Compute over RunPod, RunPod machines have terrible hard disk speeds and they are like lottery to get good ones
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Image 2, 3 and 4
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Image 2, 3 and 4
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Image 2 shows speed of our very best config FLUX Fine Tuning training shared below when doing 2x Multi GPU training
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Image 2 shows speed of our very best config FLUX Fine Tuning training shared below when doing 2x Multi GPU training
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https://www.patreon.com/posts/kohya-flux-fine-112099700
https://www.patreon.com/posts/kohya-flux-fine-112099700
link
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Image 3 shows VRAM usage of this config when doing 2x Multi GPU training
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Image 3 shows VRAM usage of this config when doing 2x Multi GPU training
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Image 4 shows the GPUs of the Pod
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Image 4 shows the GPUs of the Pod
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Image 5 and 6
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Image 5 and 6
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Image 5 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training
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Image 5 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training
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https://www.patreon.com/posts/kohya-flux-fine-112099700
https://www.patreon.com/posts/kohya-flux-fine-112099700
link
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Image 6 shows this setup used VRAM amount
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Image 6 shows this setup used VRAM amount
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Image 7 and 8
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Image 7 and 8
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Image 7 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training and Gradient Checkpointing is disabled
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Image 7 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training and Gradient Checkpointing is disabled
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https://www.patreon.com/posts/kohya-flux-fine-112099700
https://www.patreon.com/posts/kohya-flux-fine-112099700
link
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Used config name is : Quality_1_27500MB_6_26_Second_IT.json
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Image 8 shows this setup used VRAM amount
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Image 8 shows this setup used VRAM amount
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....
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I have done an extensive multi-GPU FLUX Full Fine Tuning / DreamBooth training experimentation on RunPod by using 2x A100–80 GB GPUs (PCIe) since this was commonly asked of me.

Full article here : https://medium.com/@furkangozukara/multi-gpu-flux-fu

Image 1
Image 1 shows that only first part of installation of Kohya GUI took 30 minutes on a such powerful machine on a very expensive Secure Cloud pod — 3.28 USD per hour
There was also part 2, so just installation took super time
On Massed Compute, it would take like 2–3 minutes
This is why I suggest you to use Massed Compute over RunPod, RunPod machines have terrible hard disk speeds and they are like lottery to get good ones



Image 2, 3 and 4
Image 2 shows speed of our very best config FLUX Fine Tuning training shared below when doing 2x Multi GPU training
https://www.patreon.com/posts/kohya-flux-fine-112099700
Used config name is : Quality_1_27500MB_6_26_Second_IT.json
Image 3 shows VRAM usage of this config when doing 2x Multi GPU training
Image 4 shows the GPUs of the Pod


Image 5 and 6
Image 5 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training
https://www.patreon.com/posts/kohya-flux-fine-112099700
Used config name is : Quality_1_27500MB_6_26_Second_IT.json
Image 6 shows this setup used VRAM amount


Image 7 and 8
Image 7 shows speed of our very best config FLUX Fine Tuning training shared below when doing a single GPU training and Gradient Checkpointing is disabled
https://www.patreon.com/posts/kohya-flux-fine-112099700
Used config name is : Quality_1_27500MB_6_26_Second_IT.json
Image 8 shows this setup used VRAM amount


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