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Troubleshooting

Solve common GPU acceleration issues.

GPU Detected But Using CPU

Symptom: Output shows Device: cpu even though you installed [gpu]

Solution:

  1. Verify CUDA packages are installed:
python -c "import nvidia.cublas.lib; import nvidia.cudnn.lib; print('✓ GPU packages OK')"
  1. Check your venv has GPU support:
pip list | grep nvidia

Should show nvidia-cublas-cu12 and nvidia-cudnn-cu12

  1. Verify GPU is detected by system:
nvidia-smi

Should list your GPU

  1. If still using CPU, reinstall GPU extra:
pip install --upgrade voicepad-core[gpu]

"CUDA 13 Incompatible" Error

Symptom: System has CUDA 13 installed, but voicepad mentions CUDA 12

Why this happens: faster-whisper requires CUDA 12, but your system has CUDA 13

Solution: No solution needed! The [gpu] extra installs CUDA 12 in your virtual environment, separate from system CUDA 13. They don't conflict.

  • System keeps CUDA 13 globally
  • Your venv uses CUDA 12 packages
  • Both coexist without problems

GPU Not Detected

Symptom: voicepad config system shows GPU as not available

Causes & Solutions:

Issue Check Solution
Old GPU Compute Capability < 6.0 Upgrade GPU (GTX 10-series minimum)
Old driver nvidia-smi --query-gpu=compute_cap Update NVIDIA drivers
No CUDA packages pip list \| grep nvidia Run pip install voicepad-core[gpu]

Performance Benchmarks

RTX 3050 (4GB VRAM)

  • Model: medium (recommended)
  • CPU time: ~8-10s per minute of audio
  • GPU time: ~2-3s per minute of audio
  • Speedup: 4-5x

GTX 1050 (2-4GB VRAM)

  • Model: small (recommended for limited VRAM)
  • CPU time: ~6-8s per minute of audio
  • GPU time: ~2-3s per minute of audio
  • Speedup: 3-4x

Key: Speedup depends on model size. Smaller models are faster on GPU; larger models benefit more but need more VRAM.

FAQ

Q: Do I need CUDA Toolkit installed globally? A: No. The [gpu] extra provides everything in your venv.

Q: Will GPU support conflict with my system CUDA? A: No. Virtual environment isolation prevents conflicts.

Q: Can I use AMD GPUs? A: Not currently. faster-whisper only supports NVIDIA CUDA.

Q: What about Apple Silicon (M1/M2)? A: GPU acceleration not available, but CPU mode works well.

Q: How do I disable GPU support? A: Set transcription_device: cpu in voicepad.yaml, or uninstall: pip uninstall nvidia-cublas-cu12 nvidia-cudnn-cu12

Q: Can I use uvx voicepad with GPU? A: Yes! uvx --with voicepad-core[gpu] voicepad record start

See Quick Start for installation or Advanced Setup for detailed requirements.