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    fp8 quantized Z-Image for ComfyUI using its quantization feature "TensorCoreFP8Layout".

    • Scaled fp8 weights. higher precision than pure fp8.

    • Also with "mixed precision". Important layers remain in bf16.

    There is no "official" fp8 version for z-image from ComfyUI, so I made my own.

    All credit belongs to the original model author. License is the same as the original model.


    Base

    Quantized Z-Image. Aka. the "base" version of z-image.

    https://huggingface.co/Tongyi-MAI/Z-Image

    Note: No hardware fp8, all calculations are still using bf16. This is intentional.

    Rev 1.1: An updated version with better "mixed precision". More bf16 layers, so the file is bigger. Previous version will be deleted.


    Turbo

    Quantized Z-Image-Turbo

    https://huggingface.co/Tongyi-MAI/Z-Image-Turbo

    Rev1.1: An updated version with better "mixed precision". More bf16 layers, so the file is bigger. No hardware fp8. Previous version will be deleted.

    v1: It contains calibrated metadata for hardware fp8 linear. If you GPU supports it, ComfyUI will use hardware fp8 automatically, which should be a little bit faster. More about hardware fp8 and hardware requirement, see ComfyUI TensorCoreFP8Layout.


    Qwen3 4b

    Quantized Qwen3 4b. Scaled fp8 + mixed precision. Early (embed_tokens, layers.[0-1]) and final (layers.[34-35]) layers are still in BF16.

    https://huggingface.co/Qwen/Qwen3-4B

    FAQ

    Comments (11)

    Ses_AIJan 28, 2026· 1 reaction
    CivitAI

    is fp16 available?

    GPUPoorChadJan 29, 2026· 19 reactions
    CivitAI

    6.7GBs nice

    DimSum88Feb 6, 2026· 1 reaction

    Peep the reactions

    RisingVJan 29, 2026· 1 reaction
    CivitAI

    Hi, can you confirm mixed precision checkpoint does not work with Forge Neo? I tried it with different precision settings, but only got noise images. So it's only working with comfy or am I missing something?

    reakaakasky
    Author
    Jan 31, 2026· 1 reaction

    can't tell, I don't use forge neo

    RisingVJan 31, 2026· 1 reaction

    ok...

    kevfactor859Jan 31, 2026
    CivitAI

    Im new to comfy and didn't know blackwell had advantages on certain things. i went on a deep rabbit hole chat with google and it said fp8 is better for 5080s- you only lose like 2% quality. Just curious how true that is. i thought bigger was better but i guess apparently you can add mroe steps and details to the renders going with an 8 lol

    reakaakasky
    Author
    Jan 31, 2026

    "fp8 is better for 5080s- you only lose like 2% quality"

    I would say 70% it is not true. In short, If you have a 5080 and enough vram to load the full bf16 model, you should use the full model. fp8 model is handy when vram is not enough.

    kevfactor859Feb 1, 2026

    @reakaakasky it made some case about the 5080 being better designed with the blackwell stuff to work with 8 and not loose any mor much quality. i did get a crazy workflow to like render things in about 20 seconds going to an 8 over it taking like 3-4 minutes otherwise. But in the end I ended up dropping Zimage. i couldn't get rid of my outputs having droopy faces, soemthing i had no issue with in other models. Some samplers didn't work either. I wasn't sage attention either idk

    Checkpoint
    ZImageBase

    Details

    Downloads
    1,545
    Platform
    CivitAI
    Platform Status
    Available
    Created
    1/28/2026
    Updated
    8/17/2026
    Deleted
    -