Speech Engine Comparison
whisper.cpp vs Whisper vs VOSK vs Remote API on Linux
If you are choosing a Linux speech-to-text engine, this page gives a practical side-by-side comparison focused on latency, hardware support, install footprint, privacy boundary, and real desktop usage.
whisper.cpp
- Speed
- Fastest startup + low latency
- Hardware
- CPU + AMD/Intel/NVIDIA GPU
- Accuracy
- High (best overall balance)
- Footprint
- Small models available (~74MB tiny)
- Best for
- Most users who want strong speed + quality
Whisper (OpenAI)
- Speed
- Slower install and startup
- Hardware
- CPU or NVIDIA CUDA
- Accuracy
- High
- Footprint
- Large dependency footprint (~2.3GB)
- Best for
- Users already standardized on PyTorch stack
VOSK
- Speed
- Very fast realtime on low-end systems
- Hardware
- CPU
- Accuracy
- Good for lightweight use
- Footprint
- Very lightweight (~40MB model)
- Best for
- Older hardware and minimal-resource environments
Remote API
- Speed
- Depends on server + network latency
- Hardware
- Client CPU + remote Whisper server
- Accuracy
- Depends on remote model
- Footprint
- No local model required
- Best for
- Powerful LAN servers or shared transcription backends
| Engine | Speed | Hardware | Accuracy | Footprint | Best for |
|---|---|---|---|---|---|
| whisper.cpp | Fastest startup + low latency | CPU + AMD/Intel/NVIDIA GPU | High (best overall balance) | Small models available (~74MB tiny) | Most users who want strong speed + quality |
| Whisper (OpenAI) | Slower install and startup | CPU or NVIDIA CUDA | High | Large dependency footprint (~2.3GB) | Users already standardized on PyTorch stack |
| VOSK | Very fast realtime on low-end systems | CPU | Good for lightweight use | Very lightweight (~40MB model) | Older hardware and minimal-resource environments |
| Remote API | Depends on server + network latency | Client CPU + remote Whisper server | Depends on remote model | No local model required | Powerful LAN servers or shared transcription backends |
Switching Between Engines
You can switch between whisper.cpp, Whisper, VOSK, and Remote API from Settings. v0.10.1+ safely stops recognition before switching to prevent crashes. v0.12.0 adds Remote API configuration under Advanced settings for compatible transcription servers.
When to pick whisper.cpp
Choose whisper.cpp when you want the best speed-to-accuracy ratio and broad hardware support. It is the default in Vocalinux for a reason. Safe engine switching - v0.10.1+ stops recognition before switching to prevent crashes.
When to pick Whisper
Choose OpenAI Whisper if your environment already depends on PyTorch/CUDA workflows and you prefer that runtime profile.
When to pick VOSK
Choose VOSK on older laptops, low-RAM systems, or lightweight VMs where small model size and minimal overhead matter most.
When to pick Remote API
Choose Remote API when a trusted server has stronger hardware, larger models, or a shared Whisper backend. Use local engines when your voice data must stay entirely on-device.
Remote setupNext steps
- Install by distro:Ubuntu,Fedora,Arch Linux.
- Use interactive install to detect your hardware and pick the best engine defaults.
- After install, tune model size, VAD sensitivity, or Remote API settings for your preferred latency and accuracy level.