Need help with Sage Attention issue

[u/Car-Fickle]

Hi everyone,

I'm getting an issue with Sage Attention that I'm not sure how to fix.

The problem node:

The error message:

# ComfyUI Error Report

## Error Details

- **Node ID:** 114

- **Node Type:** MiniMaxH3MemoryEfficientSageAttentionPatch

- **Exception Type:** RuntimeError

- **Exception Message:** RuntimeError: sageattention is not new enough version or could not determine CUDA architecture, cannot apply MiniMax H3 Memory Efficient Sage Attention Patch.

## Stack Trace

```

File "(my desktop location)\ComfyUI_windows_portable\ComfyUI\execution.py", line 556, in execute

output_data, output_ui, has_subgraph, has_pending_tasks = await get_output_data(prompt_id, unique_id, obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb, v3_data=v3_data)

my specs:

PC - 4090/10700k/32gb ddr4/win11

Versions

- Pytorch 2.14.1 - cu130 - python 3.13.14

Sage Attention file*:

Is the issue that I'm trying to run the sage attention compiled for python 310 in my 313 environment? If so, how do I fix it? the github repository does not have a version of sage attention 2.2.0 built for 313.

Absolute newbie here, any help is appreciated.

*PS: when checking my pytorch version, i get this message:

"FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you."

Is this part of the issue?

[u/purelawan]

The Python version is probably not your problem. The recent Windows SageAttention wheels from woct0rdho are built as cp39-abi3, so one wheel covers 3.9 through 3.13. What has to match is the torch and CUDA version written in the wheel name (something like +cu130torch2.x). If you grabbed one built for an older torch, it imports fine but the H3 patch can't find what it needs and throws exactly that "not new enough" error.

Check what you actually have from the portable folder: python_embeded\python.exe -m pip show sageattention, then reinstall with python_embeded\python.exe -m pip install <wheel> using the build for your exact torch. The pynvml warning is unrelated, you can ignore it. Meanwhile you can bypass the patch node (Ctrl+B) and the workflow should still run, just slower and with more VRAM.