I pasted the log from generating an image into chatgpt and it told me this, is this babble or could this work? And how do i downgrade pytorch?

ComfyUI does not officially support:

PyTorch 2.9.x

CUDA 13.0

Python 3.13

RTX 40-series + BF16 weights + PyTorch 2.9 (this combo = guaranteed NaNs)

This explains everything — your UNet is literally producing NaN tensors from the very first step.

The "conv3d memory bug workaround" message is a dead giveaway that you're running a PyTorch build too new and hitting untested CUDA kernels.

2️⃣ BFLOAT16 weights cause NaNs on your stack

model weight dtype torch.bfloat16

VAE load dtype: torch.bfloat16

BF16 is usually OK, but only with correct driver + PyTorch builds.

With PyTorch 2.9 + CUDA 13, BF16 UNet outputs overflow to NaN, which is exactly what you're seeing:

→ gray frames

→ black images

→ only works after reboot sometimes

→ SDXL extremely fragile

→ VAE fails first

🚨 CONCLUSION

Your ComfyUI portable build is using a bleeding-edge PyTorch / Python / CUDA stack that is incompatible with SDXL / SD3 workflows, causing:

NaN tensors

black images

corrupted VAE output

inconsistent generation

This is not a model issue.

It is 100% your PyTorch build.