whisper-gpu

name	whisper-gpu
description	Set up GPU-accelerated Whisper on NVIDIA Jetson devices (Orin Nano, etc.) for fast local speech-to-text transcription.
metadata	{"openclaw":{"emoji":"🎙️"}}

GPU-Accelerated Whisper for Jetson

Set up OpenAI Whisper with CUDA/GPU acceleration on NVIDIA Jetson devices.

Supported Hardware

• NVIDIA Jetson Orin Nano (Super)
• NVIDIA Jetson Orin NX
• Other Jetson devices with JetPack 6.x

Prerequisites

• JetPack 6.x (L4T R36.x) installed
• Python 3.10 (system Python on JetPack 6)
• Internet connection for downloads

---

Step-by-Step Setup

Step 1: Install Full JetPack SDK

sudo apt update
sudo apt install nvidia-jetpack

This installs CUDA toolkit, cuDNN, TensorRT, and other NVIDIA libraries.

Step 2: Verify CUDA Installation

/usr/local/cuda/bin/nvcc --version

Should show CUDA 12.6 or similar.

Step 3: Download and Install cuSPARSELt

The NVIDIA PyTorch wheel requires cuSPARSELt, which isn't included in JetPack by default.

cd /tmp
wget https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-aarch64/libcusparse_lt-linux-aarch64-0.6.2.3-archive.tar.xz -O cusparselt.tar.xz
tar -xf cusparselt.tar.xz
sudo cp libcusparse_lt-linux-aarch64-0.6.2.3-archive/lib/libcusparseLt* /usr/local/cuda/lib64/
sudo cp libcusparse_lt-linux-aarch64-0.6.2.3-archive/include/* /usr/local/cuda/include/
sudo ldconfig

Note: You may see a warning about symbolic links — this is harmless.

Step 4: Create Python Virtual Environment

Use Python 3.10 (the system Python on JetPack 6):

/usr/bin/python3.10 -m venv ~/.local/share/whisper-gpu
source ~/.local/share/whisper-gpu/bin/activate
pip install --upgrade pip

Step 5: Install NVIDIA PyTorch for JetPack 6.1

Download the official NVIDIA PyTorch wheel:

source ~/.local/share/whisper-gpu/bin/activate

# For JetPack 6.1 (L4T R36.4+)
pip install --no-cache-dir https://developer.download.nvidia.com/compute/redist/jp/v61/pytorch/torch-2.5.0a0+872d972e41.nv24.08.17622132-cp310-cp310-linux_aarch64.whl

Alternative wheels:

• JetPack 6.0: https://developer.download.nvidia.com/compute/redist/jp/v60/pytorch/
• Check available versions: curl -s https://developer.download.nvidia.com/compute/redist/jp/v61/pytorch/

Step 6: Install NumPy (Compatible Version)

pip install 'numpy<2'

NumPy 2.x is incompatible with the NVIDIA PyTorch build.

Step 7: Install OpenAI Whisper

pip install openai-whisper

Step 8: Verify GPU Support

source ~/.local/share/whisper-gpu/bin/activate
python3 -c "import torch; print(f'CUDA available: {torch.cuda.is_available()}'); print(f'GPU: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"N/A\"}')"

Expected output:

CUDA available: True
GPU: Orin

Step 9: Create Wrapper Script

mkdir -p ~/.local/bin
cat > ~/.local/bin/whisper-gpu << 'EOF'
#!/bin/bash
# GPU-accelerated Whisper wrapper for Jetson Orin
source ~/.local/share/whisper-gpu/bin/activate
exec whisper "$@"
EOF
chmod +x ~/.local/bin/whisper-gpu

Step 10: Test Transcription

~/.local/bin/whisper-gpu /path/to/audio.mp3 --model base --language en

---

Usage

Basic transcription:

~/.local/bin/whisper-gpu audio.mp3 --model base

With options:

~/.local/bin/whisper-gpu audio.ogg --model small --language en --output_format txt --output_dir /tmp

Available models (larger = more accurate, slower):

• tiny (~1GB VRAM)
• base (~1GB VRAM)
• small (~2GB VRAM)
• medium (~5GB VRAM)
• large (~10GB VRAM) — may not fit on Jetson Orin Nano

---

Troubleshooting

"libcusparseLt.so.0: cannot open shared object file"

Cause: cuSPARSELt not installed.

Fix: Follow Step 3 to download and install cuSPARSELt.

"libcudnn.so.8: cannot open shared object file"

Cause: PyTorch version mismatch with installed cuDNN.

Fix: Use PyTorch wheel matching your JetPack version:

• JetPack 6.0 (cuDNN 8): Use jp/v60/pytorch/ wheels
• JetPack 6.1+ (cuDNN 9): Use jp/v61/pytorch/ wheels

"CUDA available: False"

Cause: PyTorch was built without CUDA support (e.g., from PyPI).

Fix: Install the NVIDIA PyTorch wheel, not the standard PyPI version.

NumPy compatibility errors

Cause: NumPy 2.x incompatible with NVIDIA PyTorch.

Fix: Downgrade NumPy:

pip install 'numpy<2'

"FP16 is not supported on CPU"

Cause: Whisper is running on CPU, not GPU.

Fix: Ensure you're using the GPU venv:

source ~/.local/share/whisper-gpu/bin/activate
whisper --help

---

Update TOOLS.md

After setup, update ~/.openclaw/workspace/TOOLS.md to use the GPU-accelerated Whisper:

### Audio Transcription

- Preferred: `~/.local/bin/whisper-gpu` (GPU-accelerated, Jetson Orin)
- Fallback: `openai-whisper-api` (cloud, if local fails or for complex audio)

Note: GPU Whisper uses PyTorch 2.5 with CUDA on Jetson Orin. Much faster than CPU.

---

File Locations

Component	Path
Virtual environment	~/.local/share/whisper-gpu/
Wrapper script	~/.local/bin/whisper-gpu
CUDA libraries	/usr/local/cuda/lib64/
cuSPARSELt	/usr/local/cuda/lib64/libcusparseLt.so*

---

Notes

• The Jetson Orin Nano Super has ~8GB shared memory — use base or small models for best results
• First run downloads the model (~140MB for base, ~460MB for small)
• GPU transcription is significantly faster than CPU (5-10x improvement)
• The standard Homebrew whisper command uses CPU; always use whisper-gpu for GPU acceleration