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

    FAQ

    Comments (3)

    coochieJul 18, 2026
    CivitAI

    Is this basically an --int8 --scaling_mode row --convrot with convert_to_quant and leaving the simple flag off with default SVD quantization?

    WeazeJul 19, 2026· 1 reaction
    CivitAI

    Face ID with Reactor Included ? Serious ? No Thank You.

    kossanJul 20, 2026
    CivitAI

    Would you mind making one of raw? Since many people use Raw + Turbo lora combo.

    Checkpoint
    Krea 2

    Details

    Downloads
    157
    Platform
    CivitAI
    Platform Status
    Deleted
    Created
    7/18/2026
    Updated
    7/24/2026
    Deleted
    7/23/2026

    Files

    krea2RawBaseInt8Row_v10.safetensors