#7061 CUDA GPU acceleration unavailable. Verify NVIDIA GPU & CUDA installation (Help -> CUDA Help).

103.29**7 Posted at: 52 minutes ago

CUDA GPU acceleration unavailable. Verify NVIDIA GPU & CUDA installation (Help -> CUDA Help).


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system:Windows-10-10.0.26200-SP0
version:v4.11
frozen:True
language:en
root_dir:C:/Users/SF/Downloads/Compressed/win-pyvideotrans-v4.11

1 Replies

#1 DeepSeek reply at 51 minutes ago

This error means the software could not detect an NVIDIA GPU or a compatible CUDA/cuDNN environment, so GPU acceleration cannot be used. This is not a software bug — it's a system-level dependency issue.

Steps to resolve:

  1. Check if you have an NVIDIA GPU

    • GPU acceleration only works with NVIDIA GPUs. AMD/Intel GPUs are not supported.
    • Press Win + R, type dxdiag, and check the "Display" tab. If you see a non-NVIDIA GPU or only an integrated graphics card, CUDA acceleration is impossible.
  2. Verify CUDA version

    • Open Command Prompt (CMD) and run:

      nvcc -V
    • The output must show version 12.8 or higher. If nvcc is not found, CUDA Toolkit is not installed.
  3. Verify cuDNN version

    • cuDNN must be version 9.11 or higher. It is not included in nvcc -V — check the bin and lib directories under your CUDA installation path.
  4. Check NVIDIA driver

    • Run:

      nvidia-smi
    • This shows your driver version and the highest CUDA version it supports. Ensure the driver is recent enough to support CUDA 12.8+.
  5. Configure environment variables

    • If CUDA/cuDNN is installed but you still see this error, verify the PATH environment variable includes:

      • C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin
      • C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\lib
    • Add them if missing, then restart sp.exe.
  6. If you do not have an NVIDIA GPU

    • Simply uncheck the "CUDA加速" option in the main interface. The software will fall back to CPU processing, which is slower but fully functional.

Additional notes:

  • The pre-packaged version does not come with CUDA/cuDNN — you must install them separately following the guide.
  • For detailed installation steps, see the official CUDA/cuDNN setup document.

Please refer to the relevant documentation:

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