**Black Screen Update 1/2/26 - Apparently, ComfyUI might need to be told to use FP32. Here's how to do it with launch arguments. <code>--force-fp32</code> is used in ComfyUI to force all models (U-Net, VAE, and text encoder) to use 32-bit floating-point precision, which can resolve issues like black images or garbled noise in generations, particularly with certain GPUs or models like the Z-Image. How to use <code>--force-fp32</code> ** Black Screen issues - Some people have issues where it generates a black image. this has to do with the original script, and I'm not sure what causes this. I have tested it on a 4090 and 5090, and even with ALL the same drivers and Pytorch/CUDA, the 5090 gives me the black screen, but not the 4090 - if it gives you a black screen, take note of the hardware you are using and possibly try a different GPU such as the 4090. There is a clear bump in quality. If not, hang in there until we get the full weights, or someone else puts out another FP32 version. Z-Image already looks great, so this probably isn't going to be a game changer for you, but it does look a bit better. <a target="_blank" rel="ugc" href="https://github.com/PixWizardry/ComfyUI_Z-Image_FP32">https://github.com/PixWizardry/ComfyUI_Z-Image_FP32</a> Edit: also uploaded to Huggingface for transparency <a target="_blank" rel="ugc" href="https://huggingface.co/cutecaption/Z-Image_Turbo_FP32_Merged/tree/main">https://huggingface.co/cutecaption/Z-Image_Turbo_FP32_Merged/tree/main</a> By utilizing this specialized merge script, I was able to merge all of the original full precision pytorch model files on the official Z-Image Turbo: <a target="_blank" rel="ugc" href="https://huggingface.co/Tongyi-MAI/Z-Image-Turbo/tree/main/transformer">https://huggingface.co/Tongyi-MAI/Z-Image-Turbo/tree/main/transformer</a> By taking these 3 files and merging them together, we have merged it into a full precision (FP32) safe tensors file. This should in theory allow a slight bump in quality and precision. The difference between BF16 and FP32 may not be very significant and this is yet to be determined by testing, but there may be some significant use for this during LoRA training, but this is also yet to be seen. Either way, this allows us to test the model in FP32, whereas all of the previous models released appear to have been BF16 or FP8. Please note the readme information provided by the original script creator. ** I uploaded it to huggingface as well just for transparency, the hash thingies or whatever should match since it's literally the same file.

Z-Image Turbo | FP32 (Safetensors) *Fix Available*

FP32 merge of Z-Image Turbo official [3] pytorch models.

Files with SHA256: 08bf17e2411f7fab715a9a928b6b869c2d802b08d2d34c17055b981d284a09cd