CivArchive
    Krea 2 Raw / Base Int8 Row ConvRot HQ - v1.0
    Preview 137107010
    Preview 137107189

    This is HQ Int8 Row ConvRot of Krea 2 Raw (Base slow) model.

    Made from official BF16 model with SECourses Musubi Trainer Quantization app

    You can download and use Musubi Trainer app for both training and quantization from here : https://www.patreon.com/SECourses/posts/secourses-musubi-137551634

    To be able to use this model with very best performance please use our Torch 2.13 CUDA 13 ComfyUI installer with ready presets : https://www.patreon.com/SECourses/posts/download-comfyui-installers-and-presets-105023709

    I also recommend our SwarmUI installer with ready SwarmUI presets : https://www.patreon.com/posts/download-swarmui-installer-and-presets-114517862

    Int8 ConvRot is 96.2% similar to BF16 meanwhile GGUF Q8 is only 90.0% and FP8 Scaled is 82.2% and NVFP4 is 63.7%

    • Moreover, Int8 ConvRot generates the output in 3.05 seconds, making it 1.82× faster than BF16, which takes 5.56 seconds.

    • NVFP4 takes 3.8 seconds and is 1.46× faster than BF16, whereas GGUF Q8 takes 6.06 seconds and is approximately 8.3% slower than BF16.

    • So Int8 ConvRot generated with our Musubi Trainer app at high quality is almost 100% faster and almost same quality as BF16

    • High quality generation takes few hours on RTX 5090

    With our ComfyUI backend, Int8 Row ConvRot is able to generate faster than FP8 Scaled literally 100% faster on RTX 3000, 4000 and 5000 series GPUs

    Model quantization is taking around 3-4 hours on RTX 5090 since we do training like quantization with prodigy optimizer

    Check model screenshots to see and learn more

    Description

    This is HQ Int8 Row ConvRot of Krea 2 Raw (Base slow) model.

    Made from official BF16 model with SECourses Musubi Trainer Quantization app

    You can download and use Musubi Trainer app for both training and quantization from here : https://www.patreon.com/SECourses/posts/secourses-musubi-137551634

    To be able to use this model with very best performance please use our Torch 2.13 CUDA 13 ComfyUI installer with ready presets : https://www.patreon.com/SECourses/posts/download-comfyui-installers-and-presets-105023709

    I also recommend our SwarmUI installer with ready SwarmUI presets : https://www.patreon.com/posts/download-swarmui-installer-and-presets-114517862

    Int8 ConvRot is 96.2% similar to BF16 meanwhile GGUF Q8 is only 90.0% and FP8 Scaled is 82.2% and NVFP4 is 63.7%

    • Moreover, Int8 ConvRot generates the output in 3.05 seconds, making it 1.82× faster than BF16, which takes 5.56 seconds.

    • NVFP4 takes 3.8 seconds and is 1.46× faster than BF16, whereas GGUF Q8 takes 6.06 seconds and is approximately 8.3% slower than BF16.

    • So Int8 ConvRot generated with our Musubi Trainer app at high quality is almost 100% faster and almost same quality as BF16

    • High quality generation takes few hours on RTX 5090

    With our ComfyUI backend, Int8 Row ConvRot is able to generate faster than FP8 Scaled literally 100% faster on RTX 3000, 4000 and 5000 series GPUs

    Model quantization is taking around 3-4 hours on RTX 5090 since we do training like quantization with prodigy optimizer

    Check model screenshots to see and learn more

    Checkpoint
    Krea 2

    Details

    Downloads
    96
    Platform
    CivitAI
    Platform Status
    Available
    Created
    7/18/2026
    Updated
    7/19/2026
    Deleted
    -

    Files

    krea2RawBaseInt8Row_v10.safetensors