Floating point exception with nightly PyTorch and CUDA #11945
Description
Describe the bug
When running any code snippet using diffusers it fails with floating point exception, and doesn't print any traceback.
For example this one would cause the issue (the example of Stable Diffusion 3.5 medium):
import torch
from diffusers import StableDiffusion3Pipeline
pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium", torch_dtype=torch.bfloat16)
pipe = pipe.to("cuda")
image = pipe(
"A capybara holding a sign that reads Hello World",
num_inference_steps=40,
guidance_scale=4.5,
).images[0]
image.save("capybara.png")
The issue could be with upstream PyTorch or CUDA, but we'd need to identify what of Diffusers is causing it.
Reproduction
Not too sure as it's my first time with Diffusers but as suggested by John6666 any NVIDIA GeForce RTX 5000 series... In my case it's a 16gb 5060 Ti. Perhaps CUDA 575.57.08 with CUDA version 12.9 and/or PyTorch 2.9.0.dev20250716+cu129?
Logs
Let me know how can I retrieve any logs you might need.System Info
diffusers-cli env also causes a Floating point exception, but here you have environment information:
OS: Debian 12
nvidia-smi
Wed Jul 16 15:58:48 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 575.57.08 Driver Version: 575.57.08 CUDA Version: 12.9 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GeForce RTX 5060 Ti On | 00000000:01:00.0 On | N/A |
| 0% 42C P5 4W / 180W | 10MiB / 16311MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
pip list
Package Version
------------------------ ------------------------
bitsandbytes 0.46.1
certifi 2025.7.14
charset-normalizer 3.4.2
diffusers 0.34.0
filelock 3.18.0
fsspec 2025.7.0
hf-xet 1.1.5
huggingface-hub 0.33.4
idna 3.10
importlib_metadata 8.7.0
Jinja2 3.1.6
MarkupSafe 3.0.2
mpmath 1.3.0
networkx 3.5
numpy 2.3.1
nvidia-cublas-cu12 12.9.1.4
nvidia-cuda-cupti-cu12 12.9.79
nvidia-cuda-nvrtc-cu12 12.9.86
nvidia-cuda-runtime-cu12 12.9.79
nvidia-cudnn-cu12 9.10.2.21
nvidia-cufft-cu12 11.4.1.4
nvidia-cufile-cu12 1.14.1.1
nvidia-curand-cu12 10.3.10.19
nvidia-cusolver-cu12 11.7.5.82
nvidia-cusparse-cu12 12.5.10.65
nvidia-cusparselt-cu12 0.7.1
nvidia-nccl-cu12 2.27.5
nvidia-nvjitlink-cu12 12.9.86
nvidia-nvshmem-cu12 3.3.9
nvidia-nvtx-cu12 12.9.79
packaging 25.0
pillow 11.2.1
pip 23.0.1
pytorch-triton 3.4.0+gitae848267
PyYAML 6.0.2
regex 2024.11.6
requests 2.32.4
safetensors 0.5.3
setuptools 66.1.1
sympy 1.14.0
torch 2.9.0.dev20250716+cu129
torchaudio 2.8.0.dev20250716+cu129
torchvision 0.24.0.dev20250716+cu129
tqdm 4.67.1
triton 3.3.1
typing_extensions 4.14.1
urllib3 2.5.0
zipp 3.23.0
Don't hesitate to tell me any other info you might need.
Who can help?
No response